The New Platform HANA Database Overview.pdf

PUBLIC
SAP Digital Business Service China
Lecture: The New Platform
HANA Overview

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Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAm Solution
Overview in the Digital Age
2 hours
Lecture : q he Digital Core
Next Generation ERP – S/4
HANA
2 hours
Hands - On
S/4 HANA – Sim ple Finance
2 hours
Hands - On
S/4 HANA – Sim ple Logistics
2 hours
Lecture : q he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
– SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work F
Design T hink ing
4 hours
Hands - On (group work F
Conceptual Prototype
4 hours
Hands - On (group work F
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work F
Presentation of Final Result
4 hours
Lecture : q he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive N
Basic Modelling
2 hours
Hands - On: HANA Deep dive O
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
O hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
O hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 – System of Record Semester 2 – System of Innovation
Hands - On
Solution Manager 7.2
O hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

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▪ Database Overview
▪ SAP HANA Technology Innovation
▪ SAP HANA Features & Business Value
Agenda

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Course Goals
This course will prepare you to ：
? Get an overview of Database
? Understand Technology of Row - Store and Column - Store
? Understand Technology of Parallelization
? Get an overview of SAP HANA Business Value

Database Overview

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What is Database?
‡ A book?
‡ A spreadsheet?
‡ A menu on the table in the restaurant?
‡ A Database is a collection of data that is related to a particular topic or purpose.
As an example, employee records in a filing cabinet, a collection of sales leads in
a notebook, are examples of collections of data or databases.

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Why do we need Database?
‡ Do you find yourself entering the same values of information into multiple
spreadsheets/reports/documents?
‡ When you make the changes in your spreadsheet/reports/documents, are you
forced to make the same changes in others?
‡ Do you have a large amount of data that is becoming larger and unmanageable?
‡ Do several people in your organization have the need to view your data at the
same time?
‡ When viewing your information, are you constantly scrolling on your screen to
view it all? Or do you have a difficult time viewing the specific sets of data that you
want?

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Advantages of Database
‡ Data Independence/Reduced Maintenance
‡ Improved Data Sharing
‡ Increased Application Development Productivity
‡ Enforcement of Standards
‡ Improved Data Quality (Constraints)
‡ Better Data Accessibility/ Responsiveness
‡ Security, Backup/Recovery, Concurrency
Since database is that good ,
how to make a database?

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Tables
‡ Using tables is the best way to store structured data.
‡ They consist of rows and columns.
‡ Columns possess headers defining the data type stored in them and
the name with which the column can be addressed.
‡ Rows hold the actual attribute which are stored in the database.
‡ Each row is uniquely identified by a Primary Key that is represented
by one or more columns.
‡ A Foreign Key points to a column or a set of column in another
(referenced) table.
1
2
3
4
0
P F

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Transactions and the ACID principle
A Transaction is an indivisible unit of processes such as reads and writes.
ACID is an acronym for A tomicity , C onsistency , I solation and D urability.
‡ Atomicity: A Transaction fails even if only one part of it fails.
‡ Consistency: A Transaction brings the database from one consistent state to
another.
‡ Isolation: Transactions cannot interfere with each other.
‡ Durability: Data changed by committed Transaction are persisted, even after a
power loss or error.

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Indexing the data
‡ Returning the result of a query for a large dataset can take
a considerable time.
‡ Introducing indices is an option to counteract this trend.
‡ Definition: A data structure improving the search
performance of a database.
‡ It stores the values of the indexed column and a pointer to
the row which it is contained in.
‡ The cost of faster searches are a slower write performance
and higher disk space consumption.
Think of an index
as the index of a
book w ith
pointers to the
topics of interest.

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Components of a database
Data
Files
Direct User
Queries
Application
Programs

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Components of a database
Data
Files
Query Processor
Direct User
Queries
Application
Programs

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Components of a database
Data
Files
Query Processor
Direct User
Queries
Application
Programs
File Manager
Database Manager

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Components of a database
Data
Files
Query Processor
Direct User
Queries
Application
Programs
File Manager
Database Manager

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Components of a database
Data
Files
Query Processor
Direct User
Queries
Application
Programs
File Manager
Authorizati
on Tables
Database Manager
Concurrent
Access
Tables

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Components of a database
Data
Files
Query Processor
Direct User
Queries
Application
Programs
Database
Administrat
or
DDL Processor
Database
Description
Tables
File Manager
Authorizati
on Tables
Database Manager
Concurrent
Access
Tables

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Components of a database
Data
Files
Query Processor
Parameter
Files
Direct User
Queries
Application
Programs
Database
Administrat
or
DDL Processor
Database
Description
Tables
File Manager
Authorizati
on Tables
Database Manager
Concurrent
Access
Tables

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Query Execution Plan
The path how a query is being executed to return the correct result.
Show me
the song
with ID 454
Jump to table SONGS, search for record with ID
454 and give back all its fields!
SONGS

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Query Execution Plan of Traditional DB (DB6)

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Query Execution Plan of HANA DB

SAP HANA Technology Innovation
 In Memory Technology Overview
 What is SAP HANA
 SAP HANA Technolog
 Column Store & Row Store
 Parallelization
 Delta Merge

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Motivation
³ Imagine you feel hungry . But instead of just opening the fridge (imagine you GRQ¶W have one)
to get hold of, say, some butter and cheese, you would have to leave the house for the nearest
dairy farm . Each time you feel hungry . This is what we do today with most company data : We
keep them far away from where we process them « ´ *
± Prof. Norbert Walter
* Quote from the new book In-Memory Data Management by H. Plattner and A. Zeier

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In Memory Computing
Programming against a new scarce resource… Memory
Core
CPr
Disk
CPU Cache
Main Memory
… requires cache - conscious data - structures and algorithms.

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Performance Bottleneck
Core
CPU
Performance bottleneck today:
CPU waiting for data to be
loaded from memory into cache
Performance bottleneck in the past:
Disk I/O
Disk
CPU Cache
Main Memory

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SAP HANA In - Memory Computing
Hardware and Software Innovations
Innovations in
Hardw are - technology
y ~1 TB RAM / Server
y Significant Reduction in cost
/ GB
y Multi - Core Architecture
y Massive scaling with blade
servers
y Row - and column based
data store
y Compression
y Partitioning
y No pre - calculated
aggregates required
Innovations in
SAP - Softw are - technology
6$3 +$1$¶V VWUHQJWKFRPHVIURPLQQRYDWLRQVLQKDUGZ DUHDQGVRIWZ DUH
Important to understand them for understanding performance

SAP HANA Technology Innovation
y In Memory Technology Overview
y What is SAP HANA
y SAP HANA Technology
„ Column Store & Row Store
„ Parallelization & SW Side Optimization

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SAP HANA ± H igh - Performance AN alytic A ppliance
Who is it for?
y Analyze large volumes of operational data in real -
time
y Access, model, and analyze operational data in a
single environment without affecting existing
applications or systems
y Provide a high performance technological
foundation for business analytics
What is it for?
SAP HANA is a data source agonistic in - memory appliance that enables organizations to
analyze business operations in real - time based on large volumes of data .
Business User
Executive
Analyst

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SAP HANA
Not Just an In - Memory DB
What is SAP HANA?
SAP HANA is a preconfigured out of the box Appliance
ƒ In - Memory softw are bundled w ith hardw are delivered from the
hardware partner (HP, IBM, and others)
ƒ In - Memory Computing Engine ³,&(´
ƒ Tools for data modeling, data and life cycle management ,
security, operations, etc.
ƒ Real - time Data replication via Sybase Replication Server
ƒ Support for multiple interfaces
ƒ Content packages (Extractors and Data Models) introduced over
time
SAP
HANA
3rd Party
Replicate
ETL
SAP HANA
modeling
SQL
MDX
BICS
3rd
Party
ETL: Extract Transfer Load
BW : Business W arehouse
BI: Business Intelligence

SAP HANA Technology Innovation
y In Memory Technology Overview
y What is SAP HANA
y SAP HANA Technology
„ Column Store & Row Store
„ Parallelization
„ Delta Merge

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SAP HANA Technology
Row Store
Stores table by row, data records are available as complete lines in
one read.
ID Artist Genre Title
1 Adele soul
Rolling In
The Deep
2 Lady Gaga pop
Born this
way
3 Katy Perry house E.T.
4 Jason Mraz pop I am yours
2 Lady Gaga pop
Born this
way
3 Katy Perry house E.T.
4 Jason Mraz pop I am yours
1 Adele soul
Rolling In
The Deep
Single - record access:
SELECT * FROM Tophits ZKHUH,' µ¶

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SAP HANA Technology
Column Store
Stores table by column, columns can be accessed in one read..
ID Artist Genre Title hits
1 Adele soul
Rolling In
The Deep
352
2 Lady Gaga pop
Born this
way
216
3 Katy Perry house E.T. 183
4 Jason Mraz pop I am yours 96
1
2
3
4
Adele
Lady Gaga
Katy Perry
Jason
Mraz
soul
pop
house
pop
Rolling In
The Deep
Born this
way
E.T.
I am yours
352
216
183
96
Single - scan aggregation:
SELECT SUM(hits) FROM Tophits
∑
Result : 847

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP HANA Technology
Row Store vs. Column Store
y Data records are available as
complete tuples in one read.
Column Store
stores tables by column
Row Store
stores tables by row
Tuple1
Tuple2
Att1
Att1
Att2
Att2
Att2
ƒ Columns can be accessed in one
read

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP HANA Technology
Row Store vs. Column Store
Column Store
stores tables by column
Row Store
stores tables by row
Tuple1
Tuple2
‡ The application needs to process only one single
record at one time (many selects and /or updates of
single records).
‡ The application typically needs to access the
complete record
‡ The columns contain mainly distinct values so
compression rate w ould be low
‡ Neither aggregations nor fast searching are required
‡ The table has a small number of row s (for example
configuration tables)
‡ Calculations are typically executed on single or few
columns only
‡ The table is searched based on values of a few
columns
‡ The table has a big number of columns
‡ The table has a big number of row s and columnar
operations are required (aggregate, scan, etc.)
‡ High compression rates can be achieved because the
majority of the columns contain only few distinct values
(compared to number of rows)
Att1
Att1
Att2
Att2
Att2

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
&ROXPQ³$UWLVW´
(uncompressed)
sorted
Value ID implicity given by
sequence in which values are
stored
Value - ID sequence
One element for each row in
column
ID Artist Genre Title
1 Adele soul
Rolling In The
Deep
2 Lady Gaga pop Born this way
3 Katy Perry house E.T.
4 Jason Mraz pop I am yours
5 Adele soul
someone like
you
6 Lady gaga pop Pockerface
7 KatyPerry pop Part of me
8 Bruno Mars pop
Just the Way
You Are
9 Jason Mraz Pop Lucky
10 Katy Perry pop Wide awake
Value ID value
1 Adele
2 Bruno Mars
3 Jason Mraz
4 Katy Perry
5 Lady gaga
Dictionary
row
id
Value
id
1 1
2 5
3 4
4 3
5 1
6 5
7 4
8 2
9 3
10 4
This compression technology is called the Dictionary Compression . By
default , all column store data are dictionary compressed . Other
compression operations are executed on top of the dictionary
compression .
SAP HANA Technology
Dictionary Compression

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Product Stock
A 5
B 4
C 3
D 4
E 2
F 2
G 2
H 4
I 4
J 4
K 5
L 5
M 4
N 3
O 3
P 2
M apping to
memory
A B C D E F G H I J K L M N O P5434222444554332
A 5B 4C 3D 4E 2F 2G 2H 4I 4J 4K 5L 5M 4N 3O 3P2
OR
memory address
memory address
SAP HANA Technology
Other compression operations

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP HANA Technology
Other compression operations
Æ Compression rate depends on data distribution
Æ Decompression is not necessarily required for all operations :
i.e. max or avg
Æ Direct u pdate into compressed storage is expensive :
So Split into delta and main storage w ith periodic merges
Take Aw ays :
A B C D E F G H I J K L M N O P 5 4 3 4 2 2 2 4 4 4 5 5 4 3 3 2
A K L B D H I J M C N O E F G P 5 5 5 4 4 4 4 4 4 3 3 3 2 2 2 2
S ort

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Example : Row vs. Column Store Compression

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Example : Compression Ratio
Traditional DB SAP HANA DB
~ 1/7
~ 1/7

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SAP HANA Technology
Parallelization
ƒ Column - based storage also simplifies parallel execution
using multiple processor cores
ƒ Operations on different columns can easily be processed in
parallel execution of operations on one column can be
parallelized by dividing the column into multiple sections
that are processed by different processor cores

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SAP HANA Technology
Delta Merge

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP HANA Technology
Delta Merge

SAP HANA Features & Business Value
y SAP HANA Features
y SAP HANA Business Value Proposition

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SAP HANA Features
Response Time

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SAP HANA Features
Data Compression

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SAP HANA ± SAP W orld
MDX SQL BICSSQL
Modeling
Studio
Real ± Time
Replication
Services
Data
Services
SAP HANA
Other Applications SAP BusinessObjects
SAP NetWeaver
Business
Warehouse
SAP Business
Suite
3
rd
Party
In - Memory Computing Engine
Calculation and
Planning Engine
Row & Column
Storage
Capabilities Enabled
‡ Analyze information in real - time
‡ Create flexible analytic models
‡ Foundation for new category of
applications
‡ Minimizes data duplication
‡ High compatible to 3rd party
production and BI products

SAP HANA Features & Business Value
y SAP HANA Features
y SAP HANA Business Value Proposition

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Benefits from Business View
ƒ Real - Time Decision Making
± Fast and easy creation of ad - hoc views on business
± Access to real time analysis
ƒ Accelerate Business Performance
± ,QFUHDVHVSHHGRIWUDQVDFWLRQDOLQIRUPDWLRQIORZ LQDUHDVVXFKDVSODQQLQJ IRUHFDVWLQJSULFLQJDQGRIIHUV«
ƒ Unlock New Insights
± Remove constraints for analyzing large data volumes - trends, data mining, predictive analytics etc.
± Structured and unstructured data
ƒ Improve Business Productivity
± Business designed and owned analytical models
± Business self - service Æ reduce reliance on IT
± Use data from anywhere
ƒ Improve IT efficiency
± Handling growing data volume and complexity efficiently
± Lower landscape costs
Speed
Scale
Flexible

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Benefits of Being a REAL Time Consumer
Empty Shelves, Inef fective Pr omotions and Un - known Consumer Pr efer ences
‡ Reduction of out of stocks events resulting in: Increase in revenues by $ 400 Million
‡ Trade p romotion management uplift: Increase in revenues by $ 250 Million
‡ Real time c onsumer insights: Increase n ew product revenue by $ 200 Million
‡ Decrease total cost of ownership in IT: Reduction in costs of 30%
Advertising & Consumer Promotions
TPM
Consumer
TPM

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Use case: Lenovo
Computer Hardware ± Improved performance for the Business Intelligence Reporting
Product: BW (Business Warehouse) on HANA
Business Challenge
y Drive operational excellence in reporting Global Shipment
Process data
Technical Challenge
y Needed faster sales pipeline reporting from CRM
Benefits
y Real - time accurate reporting makes operations more efficient
and productive
y %HFRPH6$3¶V +DUGZ DUHSDUWQHU DQGVHOOVHUYHUV WR6$3 +$1$
customers
y Improve speed and hence utilization of BW reporting tools
20x report
performance
improvement
2x data
compression in
HANA from BW
60x improvement in
general BW query
performance from
hours to minutes

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Use case: Unilever ± Consumer Products
World's third - largest consumer goods company measured by 2011 revenues
Product: Performance analysis between SAP BPC(Budget Planning Control)
7.5 (classic database) versus SAP BPC 10 powered by SAP HANA
Business Challenges/Objectives
y Improve sales planning and forecasting processes
y Compare product cost with transfer pricing analysis using SAP HANA
y Improve the accuracy of product pricing and analysis of product costs
Technical Challenges
y Complex calculation models
y Processing big data volume (~200 million records size)
Benefits Estimated
y 15x faster transfer price analysis with SAP BPC 10 on SAP HANA
y Allow for w eekly, rather than quarterly, product costing processes
y Implement product pricing more accurately
Significant
Improvement
in accurately pricing
products
~15x Faster
to return results; run
200 million records in
30 seconds
Run Weekly
products cost
processes

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Use case: NBA.com
The pre - eminent men's professional basketball league in North America
Today, millions of fans around the world
visit this Web site to get their hands on the
1%$¶VODWHVWVWDWLVWLFVDQGPRUHWKDQ
\HDUV¶ ZRUWK RIKLVWRULFDOGDWD
³7KHUH¶VVXFKDULFKKLVWRU\ RIVWDWLVWLFVLQ
WKH1%$\HW ZH ZHUHQ¶WSURYLGLQJRXUIDQV
a robust enough database, because our
V\VWHPV FRXOGQ¶WKDQGOHLW´
As Senior Vice President and CIO Michael
Gliedman QRWHV³:HZRXOGVD\WR
ourselves, how do we make this
DZHVRPH"´
The answer to that question was found in
the SAP HANA® platform and its in -
memory computing technology .

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Use case: German Football Association
A Winning Team for German Football
Deutscher Fussball - Bund conducted a
detailed analysis of the top software vendors
and selected the SAP CRM rapid - deployment
solution powered by the SAP HANA platform,
running in the SAP HANA Enterprise Cloud.
DFB positioned itself for a swift and simple
implementation with the rapid - deployment
solution. The company was looking for a
solution that was quick to install, scalable,
and preconfigured, and the rapid - deployment
solution met all those needs. DFB was able to
implement the SAP CRM application in about
three months, thanks to a preconfigured
solution and a clear roadmap laid out by the
SAP Services organization

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Course Summary
You should now be able to:
9 Introduce Database
9 Sketch out Technology of Row - Store and Column - Store
9 Sketch out Technology of Parallelization
9 Introduce SAP HANA Business Value

Thank you.

PUBLIC
SAP Digital Business Service China
Hands on
HANA Deep Dive 1: Basic Modeling

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
ƒ HANA Studio Introduction ~ 10 m
ƒ HANA Modeling Introduction ~ 20 m
ƒ Exercises ~ 90 m
Agenda

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Course Goals
This course will prepare you to u
‡ Get an overview of HANA Studio
‡ Understand HANA Modeling Basic Concept
‡ Create HANA Information view

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Recap: SAP HANA In - Memory Computing
Hardware and Software Innovations
Innovations in
Hardw are - technology
y ~1 TB RAM / Server
y Significant Reduction in cost
/ GB
y Multi - Core Architecture
y Massive scaling with blade
servers
y Row - and column based
data store
y Compression
y Partitioning
y No pre - calculated
aggregates required
Innovations in
SAP - Softw are - technology
6$3 +$1$¶V VWUHQJWKFRPHVIURPLQQRYDWLRQVLQKDUGZ DUHDQGVRIWZ DUH
Important to understand them for understanding performance

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SAP HANA Studio
It is an Eclipse based tool which provides an environment for administration, monitoring, modeling and data provisioning.
Navigator
View
Administration View
Properties View
Memory Usage
CPU Usage
Disk Usage
HANA Version

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SAP HANA Studio
HANA studio Navigator Structure
Backup editor
Catalog
Content
Provisioning
Security
P rovide the information regarding currently running backup, last successful
backup, configuration details of the backup and access to backup catalog.
R HSUHVHQW+$1$¶VGDWDGLFWLRQDU\ LHDOOGDWDVWUXFWXUHV WDEOHVDQGGDWDZKLFK
can be used. C ontains a list of Schema s which is used to categorize tables
according to user defined groupings.
R epresent the design - time repository and contains information about data
models, organized in packages. E.g. information views, like Attribute, Analytic
and Calculation Views, can be found here.
P rovide data provisioning for Smart Data Access (SDA). SDA enables remote data
to be accessed as if they are local tables, without copying the data into HANA.
A llow to define audit policies, configure Password policy, Configure data volume
encryption. User and Role Management
*Supported sources : SAP IQ, SAP ASE, SAP Sybase ESP, Apache Hadoop, Teradata Database, Microsoft SQL Server, Oracle DB, IBM Puredata System

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Introduction to SAP HANA Modeling
™ Modeling refers to an activity of refining or slicing data in database tables by creating views to
depict a business scenario. The views can be used for reporting and decision making.
™ In SAP HANA, these views are known as information view s .
™ Information views use various combinations of content data (that is, nonmetadata ) to model a
business use case. Content data can be classified as follows:
‡ Attribute : Descriptive data, such as customer ID, city, and country.
‡ Measure : Quantifiable data, such as revenue, quantity sold and counters.
™ You can create the following types of information views:
‡Attribute Views
‡Analytic Views
‡Calculation Views

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OLAP
Engine
Join
Engine
Calculation Engine
Analytic
Views
Attribute
Views
Calculation
Views
SAP HANA Modeling
HANA Information View s
Attribute View :
™ Contain attributes.
™ Created based on one table or tables (with join)
Analytic View s:
™ R epresent an OLAP cube in HANA.
(Star Schema)
™ Contain attributes and measures.
™ Created based on Fact Table and
Attribute Views.
Calculation View :
™ Contain attributes and measures .
™ Created based on tables, attributes views,
analytic views, or other calculation views.
™ D efined as G raphical V iew or S cripted View .
™ Supported Nodes: Union, Join, Projection,
Aggregation, Rank
™ Recommend to create graphical calculation
view s for all analytical use cases.
* All three types of information views that you create in SAP HANA
Modeler perspective are non - materialized .

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Defining Table Join Types and Cardinality
Joining Tables
Inner Join
Returns rows when there is at least one match in both tables. Combines
records from the left and right table exactly when the specified criteria are
met. If the criteria are not met, no record is created in the result set.
Left (Right)
Outer Join
Returns all rows from the left (right) table, even if there are no matches in the
right (left) table. If records match, theyarecombined, otherwise the columns
are empty.
Referential Join
Text Join
n..1 1..1n..m
Used to join a multilingual description table to a master data table (e.g. Material_IDÆ
Description). The text join always filters on one language, and thus one needs to specify a
language column in the text table. The language is filtered based on the view settings (per
default taken from the user profile)
Semantically an inner join that assumes that referential integrity is given, that is, joining of
tables with primary keys and corresponding foreign keys.

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™ Unions are used to combine the result - set of two or more SELECT statements .
™ 8QLRQFDQµWEHXVHGLQ$WWULEXWH Analytic views , only can be realized in Calculation Views.
OLAP in SAP HANA ± Union

Exercise 1
HANA Studio - Add System

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Add System in HANA Studio and Check HANA Overview Page
Add HANA System in HANA Studio:
(1) Click Open Administration Console
(2) Click to add SYSTEM.
(3) Add Host Name .
(4) Add Instance Number .
(5) Click .
(6) Maintain User Name and Passw ord ,
FKHFNµ6WRUHXVHUQDPHDQGSDVVZRUGLQ
VHFXUHVWRUDJH¶$IWHU FKHFNLW\RX ZLOO
not be requested to fill the password
each time when you log on HANA
system.
(7) Click .
(8) Click .
*Demo: 01_Add System in HANA Studio and Check HANA Overview Page.exe; Exercise Details: Exercise 1.pptx

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Add System in HANA Studio and Check HANA Overview Page
Check HANA Overview Page:
(9) Double click system SID: PED. Then
SAP HANA Administration Console will
be opened.
(10) You can see Overview Page and
You can see General Information in this
page. Such as to find HANA version. E.g.
1.00.122.12.
*Demo: 01_Add System in HANA Studio and Check HANA Overview Page.exe; Exercise Details: Exercise 1.pptx

Exercise 2
Modeling - Create a Package

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HANA Modeling ± Create a Package
Create a Package in HANA Studio:
(1) Right - clicking on Content with the
mouse opens a shortcut menu.
(2) New - >Package; Left - clicking
Package to create a new Package.
(3) Maintain Name for Package. Like
00_Student.
(4) Maintain Description for Package.
Like 00_Student.
(5) Click to finish. Then you will
have a new package.
(6) Click to open Content then you will
see your package and other packages.
(7) Find your package with name
00_Student.
*Demo: 02_Create a Package.exe; Exercise Details: Exercise 2.pptx

Exercise 3
Modeling - Check Table Related Info

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HANA Modeling ± Check Table Related Info 1
Where to find table related info? --
Catalog:
(1) Open Catalog with left - clicking on .
Then you can see there are multiple
Schema.
(2) Open one Schema with left - clicking
on . E.g. SK1_EPM_REPL is the
Schema that we want to use today.
(3) Open Tables with left - clicking on .
The you will see all tables in this
schema.
*Demo: 03_Find Table Related Info.exe; Exercise Details: Exercise 3.pptx

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HANA Modeling ± Check Table Related Info 2
Check table SNWD_BPA Definition:
(4) Right - clicking on SNWD_BPA .
(5) Left - clicking on Open Definition . You
will see all Columns in the default page.
(6) Left - clicking on Indexes . You will see
index created status for this table.
(7) Left - clicking on the row display in
Indexes page. You will see Index Details .
(8) Left - clicking on Further Properties .
You will see further info (If has) for this
table.
(9) Left - clicking on Runtime Information .
You will see General Information for this
table.
*Demo: 03_Find Table Related Info.exe; Exercise Details: Exercise 3.pptx

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HANA Modeling ± Check Table Related Info 3
Check table SNWD_BPA Data:
(10) Right - clicking on SNWD_BPA .
(11) Left - clicking on Open Data Preview .
You will see all Data in this table. You
can see column CLIENT, NODE_KEY,
BP_ROLE, EMAIL_ADDRESS,
PHONE_NUMBER.
(12) Clicking the scroll button Column
right displays the desired screen area.
You can see column COMPANY_NAME.
(13) Get data in ascending order based
on column COMPANY_NAME. Left -
clicking on COMPANY_NAME column
then you can get data with ascending
order.
*Demo: 03_Find Table Related Info.exe; Exercise Details: Exercise 3.pptx

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HANA Modeling ± Check Table Related Info 4
Check table SNWD_BPA_CONTACT Definition:
*Step is same as steps for table SNWD_BPA.
We look at this table too due to we will use
these 2 tables in modeling later.
(14) Right - clicking on SNWD_BPA_CONTACT .
(15) Left - clicking on Open Definition . You will
see all Columns in the default page.
(16) Right - clicking on SNWD_BPA_CONTACT .
(17) Left - clicking on Open Data Preview . You
will see all Data in this table.
(18) Display the full value for column
NODE_KEY. You can double click on the line of
the column NODE_KEY to see full value as
some value are not complete displaying with
default column width.
(19) Close this page.
*Demo: 03_Find Table Related Info.exe; Exercise Details: Exercise 3.pptx

Exercise 4
Modeling - Create an Attribute View

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™ Business Scenario u Business Partner Report. This report includes Business Partner
1DPH1RGH.H\%35ROH&RPSDQ\1DPH7KHQEDVHGRQ%35ROH¶VYDOXHWRMXGJHWKLV
is Customer or Supplier.
ƒ Table SNWD_BPA : CLIENT, NODE_KEY, BP_ROLE, COMPANY_NAME, etc.
ƒ Table SNWD_BPA_CONTACT : FIRST_NAME, LAST_NAME, etc.
ƒ Join Condition: CLIENT, NODE_KEY=PARENT_KEY.
ƒ Output: CLIENT, NODE_KEY, BP_ROLE, COMPANY_NAME, FIRST_NAME, LAST_NAME;
ƒ Calculated Column: BP_ROLE_TEXT. Logic: BP_ROLE = 01 - > Supplier, BP_ROLE = 02 - > Customer.
ƒ Semantics: NODE_KEY as Key.
ƒ Exercise: HANA Attribute View
ƒ Name: AT_BUSINESS_PARTNER
HANA Modeling ± Create an Attribute View
*Demo: 04_Create an Attribute View.exe; Exercise Details: Exercise 4.pptx

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HANA Modeling ± Create an Attribute View 1
Where to create Information Views? --
Content
(1) Click for Catalog.
(2) Click for Content to find package.
(3) Right - clicking on 00_Student with
mouse.
(4) New - > Attribute View.
(5) Maintain the Attribute View Name :
AT_BUSINESS_PARTNER.
(6) Click Finish .
*Demo: 04_Create an Attribute View.exe; Exercise Details: Exercise 4.pptx

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HANA Modeling ± Create an Attribute View 2
Add Tables in Attribute View:
(7) Click to add 1
st
table in Attribute View.
(8) Type the table name to search for:
SNWD_BPA .
(9) Left - clicking on SNWD_BPA
(SK1_EPM_REPL) with mouse. (* there are
other schema also contains same table,
please choose the one in our schema
SK1_EPM_REPL).
(10) Click OK .
(11) Click to add 2
nd
table in Attribute View.
(12) Type the table name to search for:
SNWD_BPA_CONTACT .
(13) Left - clicking on SNWD_BPA_CONTACT
(SK1_EPM_REPL) with mouse.
(14) Click OK .
*Demo: 04_Create an Attribute View.exe; Exercise Details: Exercise 4.pptx

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HANA Modeling ± Create an Attribute View 3
Maintain Join in Attribute View:
(15 - 16) Join SNWD_BPA.CLIENT to
SNWD_BPA_CONTACT.CLIENT.
(17 - 18) Join SNWD_BPA.NODE_KEY to
SNWD_BPA_CONTACT.PARTNER_KEY.
Set Output Column:
(19 - 24) Set out put columns by left - clicking
on each column: CLIENT, NODE_KEY,
BP_ROLE, COMPANY_NAME,
FIRST_NAME, LAST_NAME.
*Demo: 04_Create an Attribute View.exe; Exercise Details: Exercise 4.pptx

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HANA Modeling ± Create an Attribute View 4
Create Calculated Column:
(25) Right - clicking on Calculated Columns to
add one calculated column.
(26) Left - clicking on New .
(27) Maintain Calculated Column Name :
BP_ROLE_TEXT.
(28) Maintain Data Type and Length .
(29) Maintain Expression :
if("BP_ROLE"='01','SUPPLIER','CUSTOMER').
(30) Click OK.
*Demo: 04_Create an Attribute View.exe; Exercise Details: Exercise 4.pptx

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HANA Modeling ± Create an Attribute View 5
Maintain Semantics :
(32) Set Key Column for NODE_KEY. (* You can
also use other functions in Semantics part like
µ+LGGHQ¶µ/DEHO&ROXPQ¶HWF
Save and Activate:
(33) Click to save and activate this view.
Check Job Log:
(34) As we hide the Log page, you can click
to restore the Log page. You can see Job Log is
Completed successfully.
Data Preview:
(35) Click for data preview.
(36) Click Raw Data to see the final result. (*
Here you can see BP_ROLE_TEXT column
result)
*Demo: 04_Create an Attribute View.exe; Exercise Details: Exercise 4.pptx

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? Business Scenario u Product Report.
Customer needs a report with info like product ID, Price, etc.
? Table SNWD_PD ： CLIENT, NODE_KEY, PRODUCT_ID, TYPE_CODE, CATEGORY, SUPPLIER_GUID,
CURRENCY_CODE, PRICE;
? KEY: PRODUCT_ID.
? Exercise: HANA Attribute View
? Name: AT_PRODUCT
HANA Modeling ? Create an Attribute View (Optional)
*Demo: 04_Create an Attribute View (Optional).exe

Exercise 5
Modeling - Create an Analytic View

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™ Business Scenario u Purchase Order Report. This report needs to contain info like PO
Gross Amount, Net Amount, BP Name, Product Price, etc.
ƒ Table SNWD_PO y CLIENT, PO_ID, PARTNER_GUID;
ƒ Table SNWD_PO_I y CLIENT, PO_ITEM_POS, PRODUCT_GUID, GROSS_AMOUNT, NET_AMOUNT;
ƒ Join Condition: CLIENT, NODE_KEY=PARENT_KEY;
ƒ Star Join: AT_BUSINESS_PARTNER, AT_PRODUCT to get detail info. Left Out Join, Cardinality: g n..1).
ƒ Measure: GROSS_AMOUNT, NET_AMOUNT.
ƒ Exercise: HANA Analytic View.
ƒ Name: AN_PO
HANA Modeling ± Create an Analytic View
*Demo: 05_Create an Analytic View.exe; Exercise Details: Exercise 5.pptx

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HANA Modeling ± Create an Analytic View 1
How to create an Analytic View:
1. Package - >New - >Analytic View. Name
AN_PO.
2. Add tables in Data Foundation:
SNWD_PO, SNWD_PO_I.
Set output columns as screenshot.
Join condition: CLIENT, NODE_KEY =
PARENT_KEY.
*Demo: 05_Create an Analytic View.exe; Exercise Details: Exercise 5.pptx

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HANA Modeling ± Create an Analytic View 2
How to create an Analytic View:
3. Add Attribute Views in Star Join part:
AT_BUSINESS, AT_PRODUCT.
Join : Data Foundation Left Outer Join
attribute views with Cardinality n:1. Join
condition as screenshot.
4. Ser Measures: Semantics - > Mark
GROSS_AMOUNT & NET_AMOUNT as
Measures.
5. Activate it and do data preview to
check result.
*Demo: 05_Create an Analytic View.exe; Exercise Details: Exercise 5.pptx

Exercise 6
Modeling - Create a Calculation View

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™ Business Scenario u Product and Sales Analysis Report.
This report is to get all Gross Amount and Net Amount for Product and Sales Scenario.
ƒ Used Views y AN_EPM_PROC_DETAILS, AN_EPM_SALES_DETAILS.
ƒ Output y CITY, COUNTRY, LAST_NAME, MIDDLE_NAME, FIRST_NAME, TITLE, CURRENCY, GROSS_AMOUNY,
NET_AMOUNT.
ƒ Function: Union.
ƒ Measure: GROSS_AMOUNT, NET_AMOUNT.
ƒ Exercise: HANA Analytic View.
ƒ Name: CA_PROC_SALES_BY_ANALYSIS_G
HANA Modeling ± Create a Calculation View
*Demo: 06_Create a Calculation View.exe; Exercise Details: Exercise 6.pptx

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HANA Modeling ± Create a Calculation View 1
How to create a Calculation View:
1. Package - >New - >Calculation View.
Name: CA_PROC_SALES_ANALYSIS_G.
2. Add Projections: add 2 projections here,
including 2 Analytic Views:
AN_EPM_PRODUCT_DETAILS,
AN_EPM_SALES_DETAILS.
Set output for each projection: CITY,
COUNTRY, FIRST_NAME, LAST_NAME,
GROSS_AMOUNT, NET_AMOUNT.
*Demo: 06_Create a Calculation View.exe; Exercise Details: Exercise 6.pptx

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HANA Modeling ± Create a Calculation View 2
How to create a Calculation View:
3. Add Union: union 2 projections together
as screenshot. Then map the columns
from source to target.
4. Set Measures: Add column as
Aggregated Column for
GROSS_AMOUNT, NET_AMOUNT.
5. Activate it and do Data Preview to
check result.
*Demo: 06_Create a Calculation View.exe; Exercise Details: Exercise 6.pptx

Exercise 7
Modeling - Create a Calculation View ± SQL (Optional)

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™ Business Scenario u Same as Exercise 6.
ƒ Use SQL Script Based Calculation View to realize same function.
ƒ Exercise: HANA Analytic View.
ƒ Name: CA_PROC_SALES_BY_ANALYSIS_S
HANA Modeling ± Create a Calculation View (SQL Based)
*Demo: 07_Create a Calculation View_SQL (Optional).exe; Exercise Details: Exercise 7.pptx

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HANA Modeling ± Create a Calculation View (SQL Based)
The view will be created as below.
*Demo: 07_Create a Calculation View_SQL (Optional).exe; Exercise Details: Exercise 7.pptx

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Course Summary
You should now be able to:
9 Had an overview of HANA Studio
9 Understand HANA Modeling Basic Concept
9 Create HANA Information view

Thank you.

PUBLIC
SAP Digital Business Service China
Hands on
HANA Deep Dive 2: AFL and PAL libraries

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Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

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ƒ AFL Overview
ƒ Predictive Analysis Introduction
ƒ Working with SAP HANA PAL
ƒ Working with Application Function Modeler(AFM)
ƒ Exercises
Agenda

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Course Goals
This course will prepare you to u
‡ Basic approach for predictive analysis
‡ Classic predictive analysis algorithm
‡ Hands - on exercise to predict potential customers for buying a
caravan insurance policy

AFL Overview

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SAP HANA is much more than just a Database

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Predictive Analytics Process in SAP HANA

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Application Function Library in General
Application Function Library (AFL) ± w hat is it?
ƒ Pre - delivered commonly utilized business, predictive and other types of algorithms for use in projects
or solutions that run on SAP HANA. The technology framework enabling the use of these algorithms
is called the Application Function Library.
:KDWDUHLW¶VEHQHILWV"
ƒ These algorithms can be leveraged directly in development projects, speeding up projects by avoiding writing
custom complex algorithms from scratch. AFL operations also offer very fast performance, as AFL functions run
in the core of SAP HANA in - memory DB.
What are its primary libraries?
ƒ The Predictive Analysis Library (PAL) is a set of functions in the AFL. It contains pre - built, parameter - driven,
commonly used algorithms primarily related to predictive analysis and data mining.
ƒ The Business Function Library (BFL) is a set of functions in the AFL. It contains pre - built, parameter - driven,
commonly used algorithms primarily related to finance.

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Application Function Library(AFL) Architecture
ƒ Application Functions
± Written in C++ and delivered as AFL content by
SAP
± Predictive Analysis and Business Function Library
have been released in SPS 05 as AFL content
ƒ AFL Framew ork
± On demand library loading framework for
registered and supported libraries
ƒ Application Function Modeler(AFM)
± A graphical editor to facilitate a faster and easier
design - time process of creating the wrapper -
procedures

Predictive Analysis Introduction

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PAL in SAP HANA

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Predictive Analysis Library (PAL) - Algorithms Supported I
ƒ Association Analysis
ƒ Apriori
ƒ Apriori Lite
ƒ FP - Growth *
ƒ KORD ± Top K Rule Discovery **
ƒ Classification Analysis
ƒ CART *
ƒ C4.5 Decision Tree Analysis
ƒ CHAID Decision Tree Analysis
ƒ K Nearest Neighbour
ƒ Logistic Regression
ƒ Back - Propagation (Neural Network) **
ƒ Naïve Bayes
ƒ Support Vector Machine
* New in SPS 08
ƒ Cluster Analysis
ƒ ABC Classification
ƒ DBSCAN
ƒ K - Means
ƒ K - Medoid Clustering *
ƒ K - Medians **
ƒ Kohonen Self Organized Maps
ƒ Agglomerate Hierarchical
ƒ Affinity Propagation
ƒ Regression
ƒ Multiple Linear Regression
ƒ Polynomial Regression
ƒ Exponential Regression
ƒ Bi - Variate Geometric Regression
ƒ Bi - Variate Logarithmic Regression
** New in SPS 09 ± Names to be finalized
ƒ Time Series Analysis
ƒ Single Exponential Smoothing
ƒ Double Exponential Smoothing
ƒ Triple Exponential Smoothing
ƒ Forecast Smoothing
ƒ ARIMA *
ƒ Brown Exponential Smoothing **
ƒ Croston Method **
ƒ Forecast Accuracy Measure**
ƒ Linear Regression with Damped Trend
and Seasonal Adjust**

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Predictive Analysis Library (PAL) - Algorithms Supported II
ƒ Probability Distribution
ƒ Distribution Fit *
ƒ Cumulative Distribution Function *
ƒ Quantile Function *
ƒ Outlier Detection
ƒ Inter - 4XDUWLOH 5DQJH7HVW 7XUNH\¶V
Test)
ƒ Variance Test
ƒ Anomaly Detection
ƒ Link Prediction
ƒ Common Neighbors
ƒ -DFFDUG¶V Coefficient
ƒ Adamic /Adar
ƒ .DW]
* New in SPS 08
ƒ Statistic Functions
(Multivariate)
ƒ Covariance Matrix
ƒ Pearson Correlations Matrix
ƒ Chi - squared Tests:
- Test of Quality of Fit
- Test of Independence
ƒ F - test (variance equal test)
ƒ Other
ƒ Weighted Scores Table
ƒ Substitute Missing Values
** New in SPS 09 ± Names to be finalized
ƒ Data Preparation
ƒ Sampling
ƒ Random Distribution Sampling *
ƒ Binning
ƒ Scaling
ƒ Partitioning
ƒ Principal Component Analysis (PCA) **
ƒ Statistic Functions (Univariate)
ƒ Mean, Median, Variance, Standard
Deviation
ƒ Kurtosis
ƒ Skewness

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Association Analysis
We use it in our everyday lives

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Association Analysis
- Example

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Cluster Analysis
‡ Customer segmentation
‡ Product positioning
‡ Crime pattern analysis
‡ «

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ƒ Who is the most important customer?
Cluster Analysis
- ABC Classification

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ƒ Example
Classification Analysis
- Decision Tree Algorithms

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‡ Definition: the sum of each attribute multiplied by its weight.
‡ In the example: Calculated score for Lily:
ƒ 30000 * 0.0005 + 9 * 2 + 3 * 1 = 15 + 18 + 3 = 36
‡ Score many records for comparison and sorting
Other
- Weighted Score Tables

Working with SAP HANA PAL

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Predictive Analysis Library (PAL) Procedure Basics
The Predictive Analysis Library uses tables as the data interface. Three types of tables are used for
each PAL function:
‡ Input data table ± supplies input data to PAL functions. Each function can have one or more input data
tables.
‡ Parameter table ± supplies parameters to PAL functions. Parameters are special inputs that control what
the functions do. Each function has only one parameter table.
‡ Output data table ± holds the output results calculated by PAL functions. Each function can have one or
more output data tables.

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Predictive Analysis Library (PAL) Procedure Basics
Table Type
Definition
Data
Preparation
PAL Interface
Generation
PAL Interface
Invocation
Training Phase
Table Type
Definition
Data
Preparation
PAL Interface
Generation
PAL Interface
Invocation
Testing/
Predictiv
Phase
Training Data Set
Testing Data Set
Control Parameter
Control Parameter
Model
Predictive Result
Data Interface Input
Data Interface Output

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Predictive Analysis Library (PAL) Procedure Basics
Table Type
Def inition
‡ Training Data Set
‡ Validation Data Set
‡ Parameter Data
PAL Interf ace
Generation
‡ Generate Store Procedure
Data
Preparation
‡ Input Table Type
‡ Parameter Table Type
‡ Output Table Type
PAL Interf ace
Invocation
‡ Call Store Procedure
CREATE TYPE PAL_CART_DATA_T AS TABLE
CREATE TYPE PAL_CART_TREEMODEL_T AS TABLE
CREATE TYPE PAL_CONTROL_T AS TABLE
INSERT INTO PAL_CART_PDATA_TBL VALUES (1, 'COIL.PAL_CART_DATA_T', 'in');
INSERT INTO PAL_CART_PDATA_TBL VALUES (2, 'COIL.PAL_CONTROL_T', 'in');
INSERT INTO PAL_CART_PDATA_TBL VALUES (3, 'COIL.PAL_CART_TREEMODEL_T', 'out');
INSERT INTO PAL_CART_PDATA_TBL VALUES (4, 'COIL.PAL_CART_STATISTIC_T', 'out');
call "SYSTEM". afl_wrapper_generator ('PAL_CART_PROC', 'AFLPAL', 'CART', PAL_CART_PDATA_TBL);
INSERT INTO #PAL_CONTROL_TBL VALUES ('THREAD_NUMBER', 2, null, null);
INSERT INTO #PAL_CONTROL_TBL VALUES ('IS_SPLIT_MODEL', 1, null, null);
INSERT INTO #PAL_CONTROL_TBL VALUES ('PMML_EXPORT', 0, null, null);
CALL "_SYS_AFL".PAL_CART_PROC(TICDATA2000, #PAL_CONTROL_TBL, PAL_CART_TREEMODEL_TBL,
PAL_CART_STATISTIC_TBL) with OVERVIEW ;

Working with Application Function
Modeler(AFM)

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Application Function Modeler
- Overview
ƒ A graphical editor to facilitate a faster and easier design - time process of creating the wrapper - procedures
ƒ AFL Models are stored as repository objects and can easily be re - used as part of development workflow
Library Selection
Algorithm Selection
Parameters for table types

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Using Application Function Modeler
- Setting Input Table Format

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Using Application Function Modeler
- Setting Algorithm Parameters

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Using Application Function Modeler
- Setting Output Table Formats

Exercise
-Background

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Scenario
To identify potential
customer for buying
caravan policy
HANA Predict Analysis Sending Email
*Screenshots shown are for dem onstration purposes only and are not final product com mitments
Potential Customer
<Education>
<Age>
<Married>
<Job>
< Children >
<Income>
<Own policy#>
<Other 70 attributes>
< Caravan Policy >
Customer Records

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Data for Insurance Case
ƒ The data contains two data files. The first data file features the actual dataset: this dataset contains 5822
customer records of which 348, about 6%, had caravan policies.
ƒ Each record consists of 86 attributes, containing sociodemographic data (attribute 1 - 43) and product ownership
(attributes 44 - 86). Attribute 86, "CARAVAN: Number of mobile home policies", is the target variable.
ƒ The test or validation set contained information on 4000 customers randomly drawn from the same population.
Training
Sample
1: 348 0: 5474
Testing
Sample
1: 238 0: 3762

Exercise 1
- Caravan Insurance Policy Prediction with PAL

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Exercise in a Nutshell
¾ I . Training Part
1. Training Sample Data preparation.
2. Table Types preparation .
3. Store Procedure generation .
4. Create Column Table to store data.
5. Invoke Store Procedure.
6. Visualize the predict statistic result .

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Exercise in a Nutshell
1. Prepare Testing Sample Data.
2. Prepare Table Types.
3. Generate Store Procedure.
4. Create Column Table to store data.
5. Invoke Store Procedure.
6. Visualize the predict statistic result .
¾ II . Testing Part

Exercise 2
- Caravan Insurance Policy Prediction with AFM

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Exercise in a Nutshell
¾ I . Training Part
1. Create XS Project.
2. Create Flowgraph Model.
3. Predict Model Design and
Configuration .
4. Visualize the predict statistic result .

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Exercise in a Nutshell
¾ II . Testing Part
1. Create Flowgraph Model.
2. Predict Model Design and
Configuration .
3. Visualize the predict statistic result .

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Course Summary
You should now be able to:
9 Using PAL with SQL Script for predict analysis
9 Using AFM with graphical editor for predict analysis

Thank you.

PUBLIC
SAP Digital Business Service China
Lecture: Case Studies 1
HANA Innovation Show Case 1 ± Text Analysis

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Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

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ƒ Overview: Text on SAP HANA Platform
ƒ Search
ƒ Text Analysis
ƒ Text Mining
ƒ Implement and Customization
ƒ Show Cases
Agenda

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Course Goals
This course will prepare you to u
‡ Get an overview of Background of Text Analysis in SAP HANA
‡ Understand Search in HANA
‡ Understand Text Analysis in HANA
‡ Understand Text Mining in HANA
‡ Apply Text Analysis in HANA
‡ Understand Customization and Dictionary.

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Recap: SAP HANA is much more than just a Database

Overview: Text on SAP HANA Platform

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Background
6$3¶VWH[WDQDO\VLV WHFKQRORJ\
1997
Inxigh t spun off
from PARC, a
Xerox company
Finite - state technology
for modeling natural
language
2007
Inxigh t acquired
by Business
Objects
Integration of text
analysis technology
into BI applications
2008
Business Objects
acquired by SAP
Text analysis technology
continues to focus on BI
applications
2012
First integration
into SAP HANA
Foundation for full - text
search, BI, and sentiment
analysis applications
Today
Text analysis in
SAP HANA
Foundation for virtually
any type of unstructured
textual data processing
on the platform

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Background
Why does SAP HANA provide text analysis functionality? (1/2)
Massive amounts of unstructured data are being
Enterprise Challenges
captured in operational, CRM, maintenance,
engineering, R&D, and call center systems, as w ell as
social media, blogs, forums, e - mails, documents,...
Companies are struggling to:
y Search on unstructured text - related content
y Extract meaningful, structured information from unstructured text
y Combine unstructured with structured data
y Leverage data in real time to gauge and guide their business
strategy and solve critical problems

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Capabilities
y Native full - text and fuzzy search
y In - database text analytics
y Graphical modeling of search m odels
y Info Access ± HTML5 UI toolkit and API for JavaScript
Benefits
y Less data duplication and movement ± leverage one
infrastructure for analytical and search workloads
y Extract salient information from unstructured textual data
y Easy - to - use modeling tools ± SA P HAN A studio
y Build search applications quickly ± Info Access
Background
Why does SAP HANA provide text analysis functionality? (2/2)

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Which types of text processing capabilities are supported?
Search
In addition to string matching,
SA P HAN A features full - text
search , which works on content
stored in tables or exposed via
views. Just like searching on the
Internet, full - text search
find s terms irrespective of the
sequence of characters and
words.
T ext mining
T ext mining makes semantic
determinations about the overall
content of documents relative to
other documents. Capabilities
include key term identification
and document categorization .
T ext mining is complementary to
text analysis.
T ext analysis
Capabilities range from basic
tokenization and stemming to
more complex semantic
analysis in the form of entity
and fact extraction . T ext
analysis applies within individual
documents and is the
foundation for both full - text
search and text mining.
Background

S earch

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Search
In addition to string matching,
SA P HAN A features full - text
search , which works on content
stored in tables or exposed via
views. Just like searching on the
Internet, full - text search
find s terms irrespective of the
sequence of characters and
words.
T ext mining
T ext mining makes semantic
determinations about the overall
content of documents relative to
other documents. Capabilities
include key term identification
and document categorization .
T ext mining is complementary to
text analysis.
T ext analysis
Capabilities range from basic
tokenization and stemming to
more complex semantic
analysis in the form of entity
and fact extraction . T ext
analysis applies within individual
documents and is the
foundation for both full - text
search and text mining.
Search

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Search
Available Languages
Arabic Indonesian
Catalan Japanese
Chinese (Simplified)Korean
Chinese (Traditional)Norwegian (Bokmal)
Croatian Norwegian (Nynorsk)
Czech Polish
Danish Portuguese
Dutch Romanian
English Russian
Farsi Serbian
French Slovak
German Slovenian
Greek Spanish
Hebrew Swedish
Hungarian Thai
Italian Turkish
A full - text index ± required for Google - like searches
± is defined on a table column.
A fuzzy search - Find database content similar to
the search terms or with typos
Search with incomplete terms
Substitute with synonyms (term mapping)
Prevent duplicates

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Search
The following steps are executed on unstructured text :
File format filtering
?
?
Converts any binary document format to text/HTMi
Language detection
?
?
Identifies language to apply appropriate tokenization
and stemming
Tokenization
?
?
Decomposes w ord sequences
E.g. “card- based payment systems” ?“card” “based”“payment”
“systems”
Stemming
?
Normalizes tokens to linguistic base form
E.g. houses ? house ; ran ? run
?
Full - text index
?
?$ttaches’ to the table column

Text Analysis

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³5DEELW +ROH´ is based on the play by David Lindsay -
Abaire, who also adapted it for the screen. T he play
received a positive review when it prem iered at
Manhatta n T heater Club in 2006 and caught the
attentio n of Ms. Kidm an and her producing partn e r, Per
Saari, who decide d to option it.
Ms. Kidm an and Mr. Eck hart shared som e thou g hts
about the new film and the process of work ing with their
director, John Cam eron Mitchell.
T ext mining makes semantic
determinations about the overall
content of documents relative to
other documents. Capabilities
include key term identification
and document categorization .
T ext mining is complementary to
text analysis.
T ext miningSearch
In addition to string matching,
HAN A features full - text search
which works on content stored
in tables or exposed via views.
Just like searching on the
Internet, full - text search
find s terms irrespective of the
sequence of characters and
words.
T ext analysis
Capabilities range from basic
tokenization and stemming to
more complex semantic
analysis in the form of entity
and fact extraction . T ext
analysis applies within individual
documents and is the
foundation for both full - text
search and text mining.
Nicole Kidm an, Aaron Eck hart and µ5DEELW +ROH¶
By MEKADO MURPHY
Dan Steinb e r g/ Associate d Press
Aaron Eck hart and Nicole Kidm an at the T oronto
International Film Festival
T ORONT O ² Nicole Kidm an returns to T oronto, this
tim e in the role of both actor and producer for her latest
project, ³5DEELW +ROH´ T he film , in which she co - stars
with Aaron Eck hart, look s at a suburb a n m arried couple
who experienc e a trem endo u s loss.
Nicole Kidm an PERSON
Aaron Eck hart PERSON
MEKADO MURPHY PERSON
Dan Steinb e rg PERSON
Associate d Press ORGANIZAT ION
T ORONT O CIT Y
Nicole Kidm an PERSON
T oronto CIT Y
David Lindsay - Abair e PERSON
Manhatta n T heater Club PLACE
2006 YEAR
Ms. Kidm an PERSON
Per Saari PERSON
Ms. Kidm an PERSON
Mr. Eck hart PERSON
John Cam eron Mitchell PERSON
« «
Text Analysis

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Text Analysis
An option to the full - text index (1/3)
T ext analysis is defined on a
table column.
It is bound to full - text indexing ±
pre - processing steps are shared.
Results are stored in a table.
During pre - processing, a full - WH[WLQGH[ LVFUHDWHGZKLFK LVµDWWDFKHG ¶
as a shadow column to the indexed table column. This index can be
accessed only indirectl y , when a full - text search is performed.
In contrast, the results of text analysis are stored in the table
$ T A_<index_name> .
SA P HANA
T ext analysis
Source table
results table
Full
-
text index
Full - text
indexing
w ith text
anal y sis

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SA P HANA
Source table
Full - text
indexing
w ith text
anal y sis
Full
-
text index
T ext anal y sis
results table
File format filtering
Ð
Languag e detection
Ð
T okenization
Ð
Stemming
Ð
Part - of - Speech
Noun groups
Entit y extraction
Fact extracti o n
File format filtering
Ð
Languag e detection
Ð
T okenization
Ð
Stemming
Ð
Part - of - speech
Noun groups
Entit y extraction
Fact extracti o n
Text Analysis
An option to the full - text index (2/3)

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Text Analysis
An option to the full - text index (3/3)
The following steps may be executed on unstructured text to augment
full - text indexing:
Part - of - Speech
Ð
Î
Tags w ord categories
Examples: quick : Adj ; houses : Nn - Pl
Noun groups
Ð
Î
Identifies concepts
Examples: text data ; global piracy
Entity extraction
Ð
Î
Classifies pre - defined entity types
Examples: Winston Churchill : PERSON; U.K .: COUNTRY;
Fact extraction
Î
Relates entities ± e.g. , classifies sentiments w ith topics
Example: I love SAP HANA :
[Sentiment] I [ StrongPositiveSentiment ] love
[/ StrongPositiveSentiment ]
[Topic] SAP HANA [/Topic].[/Sentiment]

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Entity and fact extraction
T ext analysis JLYHV µVWUXFWXUH ¶ to two sorts of elements from
unstructured text :
Entities :
John Lennon was one of the Beatles.
<PERSON> John Lennon </PERSON > was one of the
<ORGANIZATION@ENTERTAINMENT > Beatles </ORGANIZATION@ENTE
RTAINMENT>.
Facts :
I love your product.
I <STRONGPOSITIVESENTIMENT> love </STRONGPOSITIVES
ENTIMENT> <TOPIC> your product </TOPIC>.
Text Analysis

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Named entity recognition (NER) seeks to locate and classify atomic
elements in text into predefined categories such as the names of
persons, organizations, locations, expressions of times, quantities,
monetary values, percentages, etc.
NER systems take an unannotated block of text:
Jim bought 300 shares of Acme Corp. in 2006.
And produces an annotated block of text:
<PERSON> Jim </PERSON> bought <QUANTITY> 300 </QUANTITY> shares of
<ORGANIZATION> Acme Corp. </ORGANIZATION> in <DATE> 2006 </DATE> .
-- Wikipedia
Text Analysis
Entity extraction = named entity recognition

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How entity extraction works
Built - in entity extraction is no t keyw ord search.
T ext analysis applies full linguistic and statistical
techniques (i.e. natural language processing) to make
sure the entities that get returned are correct.
Grammatical Parsing:
y Can we bil l you?
y Bill Smit h was the president.
Semantic Disambiguation:
y I talked to Bil l yesterda y .
y The bil l was signed into la w .
Text Analysis

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Who : People, job title, and national
identification numbers
What : Companies, organizations,
financial indexes, and products
When : Dates, days, holidays, months,
years, times, and time periods
Where : Addresses, cities, states,
countries, facilities, Internet
addresses, and phone numbers
How much : Currencies and units of measure
Generic concepts : text data , global piracy , and so on
Supported types for entity extraction
Languages :
Arabic, English, Dutch, Farsi, French, German,
Italian, Japanese, Korean, Portuguese, Russian,
Simplified Chinese, Spanish, T raditional Chinese
Text Analysis

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Fact extraction is built on top of entity
extraction and realized through rules that look for
facts ± relations between entities or states involving
an entit y .
Relationships:
y Greek o f ficials are planning to submi t a
proposa l to eurozon e finance ministers.
States:
y The W orld T rade Center station is a
transportation station in Boston,
Massachusetts, on the MB T A ¶ s bus rapid
transit Silver Line.
Text Analysis
Fact extraction

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V oice of customer
Sentiments : strong positive, weak positive, neutral, weak negative, strong negative, and problems
Requests : general and contact info
Emoticons : strong positive, weak positive, weak negative, strong negative
Profanity : ambiguous and unambiguous
*Emoticons and profanity only
Supported fact extraction (1/2)
Languages :
English, Dutch*, French, German, Italian,
Portuguese, Russian, Simplified Chinese, Spanish,
T raditional Chinese
Text Analysis

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Enterprise
Membership information
Management changes
Product releases
Mergers & acquisitions
Organizational information
Public Sector
Action & travel events
Military units
Perso n alias, appearance, attributes, relationships
Spatial references
Domain - specific entities
Language :
English
Language :
English
Supported fact extraction (2/2)
Text Analysis

Text Mining

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Search
ƒ In addition to string matching,
HANA features full - text
search which works on
content stored in tables or
exposed via views. Just like
searching on the Internet, full -
text search finds terms
irrespective of the sequence
of characters and words.
Text analysis
ƒ Capabilities range from basic
tokenization and stemming to
more complex semantic
analysis in the form of entity
and fact extraction . Text
analysis applies within
individual documents and is
the foundation for both full - text
search and text mining.
At Dresden Sem peroper D1HZ 7 DN HRQµ7 ULVWDQDQG
Isolde ¶
By ROSLYN SULCAS February 17, 2015
DRESDEN, Germ any ² 'DYLG'DZVRQ¶V QHZ³7 ULVWDQ
and Isolde ´IRUWKH'UHVGHQ Sem peroper Ballett raises
interesting questions about the full - length story ballet, a
genre m uch - loved by audiences and seldom tack led by
choreographers today.
,W¶VVXUSULVLQJWKDWWKH7 ULVWDQDQG Isolde story, a
m edieval Celtic tale that has long figured in literature,
ILOP DQGLQ: DJQHU¶VRSHUDRIWKHVDP HQDP HKDVEHHQ
VRLQIUHTXHQWO\ XVHGE\ EDOOHW/LN H³5RP HRDQG-XOLHW´LW
has instant attraction and union between lovers from
opposing cam ps, with society and history against them ,
and tragic death at its end. You can im agine what John
Crank o or Kenneth MacMillan, who brought the big, all -
guns - EOD]LQJ VWRU\ EDOOHWVOLN H³0DQRQ´DQG³(XJHQH
2QHJLQ´WRWKHZRUOG LQWKHVDQGVEDOOHWER[
offices are still thank ing them ), m ight have done with it.
Category Classical_Music
Key term s Sem peroper , W agner, ballet,
John Crank o 5R\DO %DOOHW6FKRRO«
Vodafone T urns Focus to Broadband, Seek ing to Catch
Up to Rivals
By MARK SCOT T February 16, 2015
As consum ers change the way they use their
sm artphones, surf the web and watch television,
Vodafone is finding itself in need of a face - lift. After
years of focusing heavily on its cellphone business,
9RGDIRQHEDVHGLQ%ULWDLQ DQGWKHZRUOG¶V VHFRQG -
largest m obile operator behind China Mobile based on
subscribers, is concentrating on high - speed broadband.
Once, Europeans were happy to pay for separate
cellphone, cable and pay - TV services. Now, they prefer
them bundled into a single pack age that stream s content
to any device ² a sm artphone, tablet or Internet -
connected television.
Regional rivals lik e Orange of France and Deutsche
7 HOHN RP RI*HUP DQ\KDYHP RYHGTXLFN O\ WRRIIHU«
Category T elecom m unications
Key term s Vodafone, broadband, cellphone business,
2UDQJH'HXWVFKH7 HOHN RP «
T ext mining
T ext mining makes semantic
determinations about the overall
content of documents relative to
other documents. Capabilities
include key term identification
and document categorization .
T ext mining is complementary to
text analysis.
Text Mining

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T ext mining w orks at the document level ± making semantic determinations about the overall
content of documents relative to other documents. This di f fers from text analysis, which does
linguistic analysis and extracts information embedded withi n each document.
Functions based on vector space model
y Identify similar documents
y Identify key terms of a document
y Identify related terms
y Categorize new documents based on a training corpus
Scenarios
y Highlight the key terms when viewing a patent document
y Identify similar incidents for faster problem solving
y Categorize new scientific papers along a hierarchy of topics
Text Mining

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y The text mining index is an optional
data structure that is built from the
results of text analysis.
y It is bound to the full - text indexing
and text analysis process.
Full
-
text index
T ext
analysis
results
table
Full - text
indexing with
TA and TM
T ext mining
index
TM config.
Insert
I D TITLE
Text Mining
Text Mining Index

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SAP HANA
SAP HANA architecture
Apps on SAP HANA
Applications on any
platform using SQL
via ODBC/JDBC
Store
Tables
Engines
Search Text Mining
SQL
SAP HANA Apps
Applications running
natively on / against
SAP HANA database
Preprocessor
Linguistic
processing
Entit y & fact
extraction
Metadata
Model
Studio
Modeler,
dev.
workbench
Extended Application Services (XS)
TA & TM APIs OData

Implement and Customization

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Implement Example
Steps to use text analysis in HANA(1/ 6 )
CREATECOLUMNTABLE“PRESS_RELEASES” (
“File_Name”NVARCHAR(20),
“File_Content”BLOBST_MEMORY_LOB,
PRIMARYKEY(“File_Name”));
‡ First of all, create a simple table to store a number of PDF files that contain
information from the aviation industry in the US.
‡ Load unstructured data into the table.

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‡ C reat e DIXOOWH[WLQGH[FDOOHG³3')B)7,´RQWKH%/2%FROXPQ³ File_Content ´RI
WDEOH³35(66B5(/($6(6´
Create FullText Index ³3')B)7,´ On ³35(66B5(/($6(6´ ( ³ File_Content ´ )
TEXT ANALYSIS ON
CONFIGURATION µ(;75$&7,21B&25(¶ ;
‡ Turn t H[W$QDO\VLVRQXVHWKHFRQILJXUDWLRQFDOOHGµ(;75$&7,21B&25( ¶ .
‡ R efer to the SAP HANA Developer Guide for the different configuration.
Implement Example
Steps to use text analysis in HANA(2/ 6 )

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‡ With the execution of SQL statement, a new column table is created called
$TA_PDF_FTI ($TA_< Index_Name >) that contains the result of the Text Analysis
Process.
Implement Example
Steps to use text analysis in HANA(3/ 6 )

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‡ Structure of the result table:
Column Name Description
File_Name Primary key of the table.
RULE Stores the rule package that yielded the token.
,QWKLVFDVH³(QWLW\ ([WUDFWLRQ´
COUNTER Counts all tokens across the document
TOKEN 7KHWRNHQWKDW ZDVH[WUDFWHG WKH ³ZKR´ ³ZKDW´
³ZKHUH´ ³ZKHQ´ DQG³KRZ PXFK´
LANGUAGE You can either specify a language column when
you create the fulltext index or it can be derived
from the text. In this case it was derived from
the text and is English ( en )
Implement Example
Steps to use text analysis in HANA(4/ 6 )

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‡ Structure of the result table:
TYPE 7KH7RNHQ7\SH ZKHWKHU LWLVD³ZKR´ D³ZKDW´ D
³ZKHUH´ HWF
NORMALIZED Stores a normalized representation of the token
STEM Stores the linguistic stemming information, e.g. the
singular nominative for nouns, or the indicative for
verbs. If text analysis yields several stems, only the
first stem will be stored, assuming this to be the best
match.
PARAGRAPH The paragraph number where my token is located in
the document
SENTENCE The sentence number where my token is located in
the document
CREATED_AT Creation timestamp
Implement Example
Steps to use text analysis in HANA(5/ 6 )

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‡ Pretend you work in an airline, for example Delta Air Lines, and you would like to know whether the
company you work for is mentioned in any of the press releases.
‡ <RXFDQHDVLO\ ILQGWKHDQVZHU E\ ILOWHULQJWKHFROXPQ7<3( µ25*$1,=$7,21&200(5&,$/¶DQG
72.(1 µ'HOWD$LU/LQHV¶
‡ As you can see in the screenshot below Delta Air Lines is mentioned twice in the bts201001.pdf file
(paragraphs 9 and 151), twice in bts201002.pdf (paragraphs 9 and 136) and so on.
Implement Example
Steps to use text analysis in HANA(6/ 6 )

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Dictionaries
What are dictionaries and why do you use them?
In the context of extraction,
dictionaries are user - defined
repositories of entities.
Dictionaries are used for customized information about the
entities your application must find.
Dictionaries can be used to store name variations in a
structured way that is accessible through the extraction process.
Dictionaries are language - independent* . This means that the
same entries are matched in documents of di f ferent languages.
Dictionaries are more performant than CGU L rules.
Y ou can use several dictionaries together or combine several
entity categories in one dictionar y .
* If its name is not prefixed with the name of a language (<language> - ), in which case it will only work for that
language

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Dictionaries
For which languages are dictionaries available?
Advanced language modules
- T okenization
- Stemming
- Part - of - speech tagging
- Predefined entities
English
Arabic
Chinese (simplified)
Chinese (traditional)
Dutch
Farsi
French
German
Italian
Japanese
Korean
Portuguese
Russian
Spanish
Standard language modules
- T okenization
- Stemming
- Part - of - speech tagging
Catalan
Croatian
Czech
Danish
Hebrew
Hungarian
Indonesian
Norwegian Bokmål
Norwegian Nynorsk
Polish
Romanian
Serbian (Cyrillic)
Serbian (Latin)
Slovak
Slovenian
Swedish
Thai
T urkish
Basic language modules
- T okenization
- Stemming
Greek
Dictionaries can be created for all 32 text analysis languages:

17T
PUBLIC? 2017 SAP= SE or an SAP affi l i ate company.= Al l ri ghts reserved. ?
Dictionaries
Workflow= when= using dictionaries
N Create a dictionary follow ing XM i
syntax
<?xml version="1.0" encoding="UTF - 8" ?>
< dictionar y xmlns="http://www.sap.com/ta/4.0">
<entity_categor yname=“SPORTS_EVENTS">
< entity_nam estandard_form=“World Cup 2014">
< variant name =“Brazil 2014"/>
</entity_name>
</entity_category>
...
</dictionary>
O Activate= the dictionary
If no errors are found, the dictionary= is compiled
P Include name of new dictionary in=
custom= text analysis configuration
file
A single text analysis= configuration will normally include
multiple dictionaries and extraction rule sets
4 T est the dictionary Brazi l 2014= captured= the world ? s attention.
“Brazil 2014“ ? SPORTS_EVENTp

Show Cases
- Twitter Adapter
- Fans Mining

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HANA EIM Twitter Adapter
Introduction
‡ HANA EIM Smart Data Integration provides
adapters to access source data, provision
data, replicate data, and transform data in
SAP HANA on - premise or in the cloud.
‡ With Twitter Adapter, we can easily retrieve
tweets data and perform further Text Analysis
in HANA.

Show Cases
- Twitter Adapter
- Fans Mining

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Fans Mining

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Course Summary
You should now be able to:
9 Introduce Background of Text Analysis in SAP HANA
9 Sketch out Search in HANA
9 Sketch out Text Analysis in HANA
9 Sketch out Text Mining in HANA
9 Sketch out How to use Text Analysis in HANA
9 Sketch out Customization and Dictionary

Thank you.

PUBLIC
SAP Digital Business Service China
Lecture: Case Studies 2
HANA Innovation Show Case 2 ± Big Data

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Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

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ƒ Facing Big Data
ƒ Overview: SAP Big Data Solutions
ƒ Technical Content of SAP Big Data
ƒ Business Applications of SAP Big Data
Agenda

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Course Goals
This course will prepare you to u
‡ Get an overview of Big Data
‡ Understand SAP HANA Data Solutions
‡ Get an overview of Technical Content of SAP Big Data
‡ Get an overview of Business Applications of SAP Big Data

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Reap: HANA EIM Twitter Adapter
Introduction
‡ HANA EIM Smart Data Integration
provides adapters to access source
data, provision data, replicate data,
and transform data in SAP HANA
on - premise or in the cloud.
‡ With Twitter Adapter, we can easily
retrieve tweets data and perform
further Text Analysis in HANA.

Facing Big Data

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What is Big Data?
Age of Data has come
Lots of data is being
collected and
Warehoused.
Web data,
e - commerce
purchases at
Department,
grocery stores Bank,
Credit Card,
transactions Social
Network
«

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Enterprise
Application/System
Social
Media
Log, Sensors
Mobile
Cloud
Office
Application,
Files
«UHIHUVWRGDWDVHWVZKRVHVL]HLVEH\RQGWKH
ability of typical database software tools to
capture, store, manage and analyze
What is Big Data?

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© 2016 SAP SE or an SAP affiliate company. All rights reserved.
Public
2
Ne w types of data
Sentiment
Understa n d ho w y our
custome r s feel about
y our brand and
products ± right now
Unstructured
Understa n d patterns
in files across millions
of w eb pages, emails,
and documents
Clickstream
Capture and anal y ze
w ebsite v LVLWRUVµ data
trails and optimize
y our w ebsite
Sensors
Disco v er patterns
in data streaming
automaticall y from
remote sensor and
machines
Geographic
Anal y ze location -
based data to manage
operations w here the y
occur
Ser v er Logs
Research logs to
diagnose process
failures and pre v ent
securit y breaches
What is Big Data?
Common Types of Big Data

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‡ Structured Data: Data with structure (can be represented by a table)
‡ 8QVWUXFWXUHG'DWDWH[WYLGHRDXGLRJUDSKLF«
What is Big Data?
Structured Data & Unstructured Data

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Roche Diagnostics
/LYLQJWKHKHDOWKLHUOLYHVZHGUHDPDERXW«
Objecti v es
Big Data: Digitizing O u rselves
Stopping Diabetes in Its Tracks with Connected Care
Called Accu - ChekView 5RFKH¶VQHZSDFNDJH
combines a blood glucose monitor, a wearable
fitness tracker, and an App developed by SAP
that are integrated together. Specifically targeted
to meet the individual needs of patients and
GRFWRUVQRZDSDWLHQW¶VYLWDOVLJQVDQGEORRG
sugar level can be watched in relation to their
physical activity level, in real - time. The doctor can
monitor the patient remotely, and the patient can
FRPPXQLFDWHZLWKWKHGRFWRU ¶VRIILFH

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Big Data: Co n nected Cities
Improving the qua l ity of life
The cit y of Boston
Improving the quality of life with bet t er city services
Objecti v es
y Improve the qualit y of cit y services for Boston residents
y Better align the cit y ¶ s actions and resources to
established objectives
y Ensure public transparenc y to the cit y ¶ s performance
y Better anal y tics, especiall y for the management of
buildi n g permits and licensi n g
y Use big data anal y tics to fight crime

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Big Data: Co n nected Cities
Safe r , cleane r , and more productive
The cit y of Boston
Boston is safe r , cleane r , and more producti v e
Results
y 55% less crime in targeted locations
y Less then 10 overdue cit y permits, reduced from
over 600
y 66% reduction in calls regarding problem properties
y 2000 unique KPIs being delivered via mobile and
online

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Big Data: From Noise to T rue Market Sig n als
Enabling early signal detection
BIG D A T A REVEALS
MARKE T P A TTERNS
‰ 300 analysts
‰ Predict customer bu y ing patterns
‰ 500 metrics analyzed
‰ B y SA P HAN A to select best
model 97% of the time
eBa y
Enabling early signal detection
Objecti v es
y Incr e ase abilit y to separate si g nals from nois e
to identif y ke y changes to the health of eBa y ¶ s
marketplace
y Improve predictabilit y and forecast confidence
of eBa y ¶ s virtual econom y
y Increase insights into deviations and their
causes

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Big Data: From Noise to T rue Market Sig n als
Pinpointing market signals to connect sellers and buyers
eBa y
Pinpointing market signals to connect sellers
and buyers
Results
y Automated signal detection s y stem that can
automaticall y select the best model for metrics,
increasing the accurac y of forecasts
y Reliable and scalable s y stem that provides real - time
insights, allo w ing data anal y sts to focus on strategic
tasks
y Decision tree logic and fle x ibilit y to adjust scenarios,
allo w ing eBa y to adapt the best model for its data

Overview: SAP Big Data Solutions

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SA P Big Data Solutions
Needs and challenges
A A A
Acq u ire Analyze Act
Old
DB M S
Comple x
IT
Different
v arieties
Big Data
y Enterprise applications
y Documents
y Sensors and machines
y Social media
y V ideos
y Images
y W eb blogs
Real Results
y Customer demand
y Sentiment intelligence
y Fraud detection
y Predictive maintenance
y Suppl y chain optimization
Data
scientist
Emplo y ee
access
Business
operations

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SA P Big Data Solutions
The solution
HANA
A
A
A
Acquire
Data
Connectors
ETL
Streaming
Anal y tics
Advanced
Anal y tics
Agile
Visualization
Enterprise BI
Big Data
Development
Tools
Industr y
Apps
LoB Apps
Data Science
Ser v ices
Big Data Apps
& Anal y tics
SA P HAN A
P l atform for
Big Data
&
&

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Adoption made simple
y Infrastructure optimized for Big
Data processing
y Access data from an y other
source
y All data stores benefit from the
in - memor y performance
y Ensure simpl e r iteration of
application - specific models
SAP HA N A
In - Memor y / Text Anal y sis /
Predictive
SA P HAN A Platform for Big Data
Ad v anced Anal y tics Mobile & Embedded
SAP HANA e x tended application ser v ices,
data ser v ices, SAP ESP
informatio n and real - time data mo v ement
Integr
a
t
e
d
Modeling
and
Metadata
Handling
Common Data Access
OData, JSON, Smart Data Access
SAP ESP
Stream Analytics
SAP IQ
Near Line Store
A nal y tics / BI
S A P Lumira
Cloud A pps
HTML5/UI5
S A P Fiori A pps
S A P Business
Suite A pps
Custom A pps
Hadoop
M ass Data Store
Integr
a
t
e
d
S
y
stems
Management
and
Landscap
e
for
H
y
brid and
Cloud
SA P Big Data Solutions
SAP HANA platform for Big Data

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Make Big Data
insights actionable
via industry - specific,
business - f ocused
applications from S A P
Customer V alue
Intelligence
Audience
Discover y
Account
Intelligence
Fraud
Management
Demand Signal
Management
Social Contac t
Intelligence
Sentiment
Intelligence
Predictive
Maintenance
Responsive
Manufacturing
SA P Big Data Solutions
SAP industry and line - of - business applications

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y T op (PhD) level global science teams in Scottsdale, W alldorf, and Bucharest
y Credibilit y attained b y w orking w ith >100 customers and creating some of the most sophisticated use cases
y Pioneers in demand science, w ith significant reusable I P and deep anal y tic competencies
± Insights and compliance
± Mathematical modeling, forecastin g , simulation, and optimization
y Experts in relevant SA P technolog y : SA P HANA, SA P BusinessObjects, SA P Predictive Anal y sis, visualization
y Flexible deliver y
SAP HANA
platform and be y ond Data Science SAP BusinessObjects
SAP Predictive Anal y sis Dashboards
PAL and R
& &
integration



2
/(2)
()
fx
e
(x)
2
2
SA P Big Data Solutions
Data Science

Technical Content of SAP Big Data

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Explore the world of Big Data
SAP HANA Predictive
Hadoop
SAP Vora
Machine Learning
The World of SA P Big Data

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Predictive Analytics Process in SAP HANA

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$SDFKHŒ Hadoop® is an open - sourc e framework
for distributed storage and processin g of very large
data sets on computer clusters from commodit y
hardware
Used at Google, Y ahoo, Facebook, eBa y ,
LinkedIn, startups , and Fortune 500 enterprises to
store and process petaby t es of data on thousands
of servers
Hadoop components
y Cluster of commodit y servers
y Distributed storage la y er (Hadoop Distributed File
S y stem, or HDFS)
y Distributed processing infrastructure (MapReduce
programming model)
Hadoop Overview
What is Hadoop?

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Democratize
Data
Access
Make
Precision
Decisions
Simplify
Big Data
O w nership
S A P HANA Vora is an in - memory query engine that leverages
and ex t ends the Apache Spark execution framework to provide
distributed computing at scale and deli v er enriched interactive
y
y Drilldo w ns on HDFS
analytics on Hadoop.
Mashup API
Enhancements
Compiled Queries
y SA P HAN A Spark
Controller
y Open Programming
Hadoop/Spark Clusters
SAP HANA Vora Overview
S A P H A N A V ora ± What ¶ s inside and what does it do?

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Machine Learning
Introduction
³$FRPSXWHUSURJUDPLVVDLGWROHDUQIURP
experience E with respect to some class of tasks T
and performance measure P if its performance at
tasks in T, as measured by P, improves with
experience E. ´
²² Mitchell, T. (1997). Machine Learning, McGraw Hill
Artificial intelligence, machine learning, and
deep learning are often used interchangeably,
EXWWKH\¶UHQRWWKHVDPH,QDQXWVKHOO$,LVWKH
broader concept of machines that can act
intelligently. Machine learning and deep
learning are sub - sets of AI based on the idea
that given access to large volumes of data,
machines can learn for themselves.

Business Applications of SAP Big Data

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Make Big Data
insights actionable
via industry - specific,
business - f ocused
applications from S A P
Customer V alue
Intelligence
Audience
Discover y
Account
Intelligence
Fraud
Management
Demand Signal
Management
Social Contac t
Intelligence
Sentiment
Intelligence
Predictive
Maintenance
Responsive
Manufacturing
Big Data Apps & Analytics
SAP industry and line - of - business applications

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A pplication 1
³2XUGHVLJQHUVXVHGWRIROORZ
their instinct in fashion
trends, and sometimes what
WKH\FDPHXSZLWKGLGQ¶W
meet market demands. It
UHVXOWHGLQPDVVLYH VWRFN´
- Lin Yuchun , president of Aimickey
Shoe Company in the Chinese city of
Chengdu, one of the four footwear
industrial clusters in China.

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A pplication 2

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Predictive Maintenance
Based on SA P Predictive Analytics?
SA P Predictive Analytics is
y A comprehensive, leading product o f fering from SAP
y An advanced area of analytics designed to provide
more intelligent, more forward - looking (anticipatory),
and more actionable analysis
SA P Predictive Analytics is designed to
y Help companies make better decisions
y Derive better insight and optimize customer
relationships
y Make more meaningful and proactive sense of Big
Data
y Answer di f ficult questions that business intelligence is
not equipped for

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Predictive Maintenance
In - memory predictive analytics with SA P HANA
Native predictive modeling libraries (AP L and P AL)
for SA P HANA
y Classification and regression analysis
y Association analysis
y Cluster analysis
y T ime series analysis
y Outlier detection
y Link prediction
y Descriptive statistics
R integration
y R script execution
SQ L Engine
T ext Engine
Calculation Engine
In - Memory Processing Engine
APL
R
P AL
Scripts

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Application 3

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Application 4

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Course Summary
You should now be able to:
9 Introduce What is Big Data
9 Sketch out SAP Big Data Solutions
9 Introduce Technical Content of SAP Big Data
9 Introduce Business Applications of SAP Big Data

Thank you.

PUBLIC
SAP Digital Business Service China
Lecture: The Digital Core
Next Generation ERP ± S/4 HANA

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Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

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ƒ Introduction 20mins
ƒ SAP S/4 HANA 70mins
ƒ Real Customer Use Cases 15mins
ƒ Summary 5mins
Agenda

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Course Goals
This course will prepare you to u
‡ Get an overview of SAP Digital Core concept
‡ Understand key features of S/4 HANA
‡ Understand the comparison of traditional ERP and S/4HANA
‡ Understand the Enterprise Management Scope of S/4HANA
‡ Understand the components of S/4HANA

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Recap of Previous Course (SAP HANA)
S/4HANA is using
HANA as the in -
memory database.

Introduction
in the new digital and networked world

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Digital Technologies are Here to Stay
The World is Changing Quickly
Digital Technologies are Everywhere
Mobile
Social
In - Memory
Computing
Machine
Learning
Cloud
Internet
of Things
Big Data
Hyper
Connectivity
Digitization of data and interactions increasing at an
exponential pace.
Mobile, Internet of Things and Hyper - connectivity
HQDEOLQJLPPHGLDWHDFFHVVWRHYHU\ ³WKLQJ´
Cloud enabling digitization with commodity storage,
and on - demand computing at scale
In - Memory changing the speed of computing and
delivering the vision of real time
Big Data and Machine learning technologies
changing how data is being analyzed with predictive
analytics

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SAP S/4HANA
The Digital Core - reimagines businesses for the digital economy
y The entire value chain is digitized,
including the digital core that
serves as the foundation for business
innovation and optimization.
y The digital enterprise interconnects
all aspects of the value chain to drive
and anticipate business outcomes
in real time.
y Enterprises across industries can
lead the digital transformation by
completely reimagining business
models, business processes, and
w ork.

SAP S/4 HANA
- Why S/4 HANA
- S/4 HANA Enterprise Management
- Embedded Analytics & Innovation Highlights
- SAP Fiori

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Comparing Traditional ERP to the Digital Core
Traditional ERP
Siloed Data
Partially connected
Reporting tool
Digital Core
Live Business
Unified data
in real time
Fully connected to
customers, suppliers
and workforce
Intelligent, predictive
tools based on
patterns and trends
35,000
SAP customers already
have an ERP core
Covering
25
10
120
Lines of
Business
industries countries

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SAP S/4HANA
Our next - generation business suite
SAP S/4HANA Enterprise Management ±
build the next - generation business suite
» Innovative in - memory database
» New architecture and data models
» Renewed applications
» New user interface (UI) technology
» Cloud and on - premise deployment models
» Natively integrated
SAP S/4HANA is a new product line ( it is not a legal successor of any SAP Business Suite product).
The classical SAP Business Suite and SAP ERP software is a separate product line and will still be
available.
SAP Ariba l Concur I SAP Fieldglass I SAP Hybris I SAP SucessFactors
On Premise Cloud

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SAP S/4HANA and SAP Business Suite
Understanding the difference
SAP S/4HANA
Compatibility
Scope
Cloud
Editions
SAP Business Suite
On - Premise
EHP7/8
ERP
SAP
S/4HANA
Finance
On - Premise
EHP7/8
SAP S/4HANA
Finance as
innovation package
Classical ERP on
any DB incl.
HANA
Compatibility
scope to support
migration
Cloud Qualities
also available On -
Premise
SAP S/4HANA
SAP HANA only
supplies
supplies
On - Premise
Relation between SAP ERP and SAP S/4HANA

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SAP S/4HANA
The Big Picture
Modern Architecture New Design Smart Business
» People Centric
» Any Device
» Browser based
» Embedding Workflows
» Communication enabling
» Decision Support
» Robust and Scalable
» Simple Data Structures
» Speed on Primary Data
» Single source of truth
» Flexible consumption
» Non Disruptive Journey
» Built for Scalability
» Automation & IoT
» Cockpits with Exception
based Worklists
» Embedded Analytics
» Simulation
» Prediction
Innovations
» Industry to core
» aATP
» PP/DS
» EWM
» FI - CA
» MDG
» QM
» «
+ + +

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SAP S/4HANA
Next - generation business suite
Feature and function parity to
SAP ERP Central Component
(SAP ECC) 6.0x plus:
» Major innovations in core
features like finance and
logistics
» Inclusion of additional
industries in the core
» Major simplifications
https://help.sap.com/s4hana_op_1610
» Support for digital trends like
the Internet of Things,
business networks, and so on
Enterprise Management
Product lifecycle
management
Logistics execution
Materials management
Quality management
Sales and distribution
Finance
Logistics general
Plant maintenance Customer service
Production planning and
control
Project system
Environment, health,
and safety
Others: global trade
management
The
Digital
Core
Human resources
Included Features*
Included Industries*
Core industries
‡ Chem icals
‡ Life sciences
‡ W holesale and distribution
‡ High tech
‡ Mining
‡ Industrial m achinery and
com ponents
Core industries ± adding
features and processes
‡ Automotive
‡ Industrial machinery and
components
‡ Aerospace and defense
‡ Mill products
‡ Retail
‡ Oil and gas
Note: Not all features are
activated in the cloud edition.
* D oes not reflect licensing

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SAP Digital Boardroom
‡ Total transparency
‡ Instant data - driven insights
‡ Simplified boardroom processes
Logistics
Finance
SAP HANA
BW
Operations
HR
Etc
Sales
OTHER
SAP BusinessObjects Cloud
‡ Planning
‡ Business Intelligence
‡ Predictive
‡ Governance
Top Floor
SAP S/4HANA embedded analytics
‡ SAP Smart Business cockpits
‡ SAP Fiori analytical apps
‡ Predefined reports & visualizations
‡ Extensibility concept & tools
Shop Floor
From top floor to shop floor
SAP S/4HANA
From the top floor to the shop floor

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Enter Material Order
Choose best supplier
and complete material
order entry
Review Material
Shortage
Select
Supplier
Analytics and
Insights
Now All On
One Screen
Purchase
Manager
Check
Budget
Overview
Review
Detail
Report
9 Faster customer
delivery
9 Larger average deal
size
9 Fewer warehouse
stock outs
Check Average
Supplier
Delivery
Performance
Cro
ss
Sell
SAP S/4HANA
Contextual insights at the point of decision

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SAP S/4HANA
Transformational simplifications
Reduce total cost of ow nership
Increase user productivity
Accelerate execution
Simplified data model Simplified system landscape Simplified user experience
Classic SAP Business Suite
11 Inventory aggregate tables
2 Document aggregate tables
11 History aggregate tables
2 Material master tables
Role - based engagement
across the business
Instant access to any
business insight
Simple design across
business processes
SAP GUI SAP Fiori UX Delta
Duration
(seconds)
132 47 - 64%
Clicks 39 11 - 71%
Screen changes 8 2 - 75%
Fields f illed 5 2 - 60%
Example: SAP S/4HANA Finance -
receivables management
Reduced number of systems
and business warehouses
Flexible access to data and
data compression
Few er interfaces between
systems
Example: SAP S/4HANA Supply
Chain* ± inventory management
Elimination of aggregates
SAP S/4HANA
1 Document table
2 Material master tables
Simplification of master data
Unification of tables
Example: Reduced Data
Footprint**
** SAP Benchmarking Services
26 3

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SAP S/4HANA
Data footprint reduction
Database Footprint
Reduction in
SAP Finance
on HANA S/4HANA ActualTraditional DB
593 GB
118.6 GB
42.4 GB
8.4 GB
Replace totals with on - the - fly aggregation.
Replace secondary indices with dynamic
projection and selection.
Data Aging
5 fiscal years in the
system, 1 year aging
frequency
Compression in
columnar storage

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SAP S/4HANA
Key Benefits of Technology
Discover and respond to
future opportunities and
challenges
Real Time
Predictions
Eliminate batch processing,
data reconciliation
Analyze at any level
without exporting data
Simulation
Explore the impact of
business decisions on
outcomes
Built - in data driven
decision support systems
Responsive
Improve user satisfaction
by reducing wait time
Drilldow ns
Recommen -
dations

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SAP S/4HANA
Key Take Aways
Instant, real - time insight for better decisions
± in - memory technology
± embedded analytics
Reinvented processes for higher performance
± maximized throughput and speed
± native integration to SAP solutions
FIORI user experience for higher productivity
± intuitive on all devices, mobile first
± proactive decision - making support
THE NEXT GENERATION BUSINESS SUITE FOR A
DIGITAL WORLD.
Simplified Architecture for low er TCO
± lean data footprint
± cloud deployment for higher flexibility

SAP S/4 HANA
- Why S/4 HANA
- S/4 HANA Enterprise Management
- Embedded Analytics & Innovation Highlights
- SAP Fiori

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SAP S/4HANA: Enterprise Management
Complete
Cost management
and profitability
analysis
Supplier
management
Invoice and
payables
management
Inventory and
basic warehouse
management
Collaborative
sourcing and
contract
Operational
purchasing
Accelerated
plan to product
Production
engineering
Production
planning
Project control and
product
development
Production
operations
Quality
management
Inventory and
basic warehouse
management
HR
connectivity
Time
recording
Core finance
Enhanced
request to
service
Optimized
order to cash
Streamlined
procure to pay
Accounting and
closing operations
Service
management
Service parts
management
Service master
data management
Inventory and
basic warehouse
management
Receivables
processing
Order and contract
management
Service agreement
management
Maintenance
management
Procurement
analytics
160
countries
38
languages
25
industries

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SAP S/4HANA 1610
Shipment Scope
SAP S/4HANA M ARKETING AND
COM MERCE
SAP S/4HANA HUM AN RESOURCES SAP S/4HANA M ANUFACTURING SAP S/4HANA SUPPLY CHAIN
SAP S/4HANA SALES
SAP S/4HANA FINANCE
SAP S/4HANA SERVICE
SAP S/4HANA SOURCING &
PROCUREM ENT
SAP S/4HANA ASSET M ANAGEM ENT
Digital Core
Enterprise Management
SAP S/4HANA RESEARCH &
DEVELOPM ENT
Products
Suite
Products
Suite
INDUSTRIES
‡ Supplier Collaboration
‡ Business Network
‡ Guided End - User Buying
‡ External W orkforce Managem ent
‡ Core Hum an Resources And Payroll
‡ Talent Mgm t.
‡ Tim e and Attendance Mgm t.
‡ Hum an Capital Analytics
‡ Asset Operations and Maintenance*
‡ Environm ent, Health, and Safety
‡ Enterprise Portfolio and Project Mgm t.
‡ Com m ercial Project Mgm t.
‡ Com pliant Product Lifecycle Mgm t.*
‡ Service Mgm t. *
‡ Service Master Data Mgm t.*
‡ Service Parts Mgm t.
‡ Service Agreem ent Mgm t.*
‡ Maintenance Mgm t. ‡ Product Developm ent and Project
Control*
‡ Production Engineering
‡ Financial Planning and Analysis
‡ Accounting and Financial Close
‡ Treasury Mgm t.
‡ Receivables Mgm t.
‡ Invoice Mgm t. and Accounts Payable
‡ Accounting and Closing Operations
‡ Accounting
‡ Cost Mgm t. and Profitability
Analysis
‡ Tim e Recording
‡ Operational Purchasing
‡ Collaborative Sourcing and Contract Mgmt.
‡ Inv oice and Payables Mgmt.
‡ Supplier Management
‡ Procurement Analytics
‡ Production Operations
‡ Quality Mgm t.
‡ Inventory and Basic W arehouse
Mgm t.
‡ Production Planning
‡ Order and Contract Mgm t.
‡ Sales Planning and Perform ance
Mgm t. (ICM)
‡ Billing and Revenue Innovation
Mgm t. (BRIM)
S/4HANA MarketingCloud for Sales
*(partial) Compatibility Scope
‡ Financial Services Network
‡ Extended W arehouse Mgm t.
‡ Advanced ATP
‡ Constrained production planning
‡ Production Scheduling
‡ Constrained production planning
‡ Planning and Scheduling

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SAP S/4HANA Sales
ORDER AND CONTRACT
MANAGEMENT
Solution Capabilities:
E2E Business Process:
Leverage simplified data
model and central
Business Partner
approach.
Create, modif y, or display
sales documents with work
lists, m anage sales
quotations, orders, credit
and debit memo requests.
Access documents quickly
Take immediate action
using real - time analytical
results to ef fectively
manage Sales Contracts
and Sales Quotations
Identif y bottlenecks &
issues with resolution
proposals in the Sales
Order Fulfillment Cockpit
I RUPD[LPL]LQJ ³QR - WRXFK´
order rate. Leverage
w orklists with smart links
to related documents and
transactions to streamline
the f low
Settle rebate f lexibly using
Condition Contract
Settlement without any
index table.
Manage Billing Document
ef ficiently with seamless
integration to related
operational transactions
and use Intrastat
Processing f or Foreign
Trade activities
Reduce customer service &
support cost by
automating and
streamlining return
processes
Monitor Order - to - Cash
Process Performance and
execute Sales Analysis on
the f ly and d isplay
contextual inf ormation, or
analyze your sales
quotation conversion
rate , or open sales orders
and deliveries and track
overall O2C performance
in your company
SALES
MASTER DATA
MGMT.
SALES
CONTRACT
MANAGEMENT
SALES ORDER
MGMT. &
PROCESSING
BILLING &
INVOICING
CLAIMS,
RETURNS &
REFUND MGMT.
SALES
MONITORING &
ANALYTICS
Innovation & Highlights:
Use new Condition
Contract Settlement
Analyze your Sales Order
Conversion Rate
Close Open Sales quickly
and improve overall
Performance
Manage Sales contracts in
just seconds

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SAP S/4HANA Supply Chain
Optimize your stock and inventory turnover and
material flow
Track inventory situation cross entities
and over - time to react as needed
PRODUCTION
PLANNING
Solution Capabilities:
E2E Business Process:
GOODS ISSUE
GOODS
RECEIPT
BASIC
WAREHOUSE
MGMT.
BASIC
SHIPPING
MATERIAL
REQUIREMENT
S PLANNING
BASIC ORDER
PROMISING /
ATP
Innovation & Highlights:
Visualize & simulate MRP
options with fast insight to action
INVENTORY &
BASIC
WAREHOUSE
MGMT
Optimize the inventory and
material f lows with analytical
apps, to include:
‡ Inventory turnover
analysis
‡ Flow analysis
Use simplif ied GI postings
‡ Transfer and scrapping
For complex movements
use MIGO w ith One Look
Leverage simplified data
model incl. 40 digit mat - no.
For real - time, high - volume
processing you can post
with f inest granularity to
leverage sensor data.
Benef it f rom locking
elimination and material
ledger valuation.
Use simplif ied new apps f or
‡ GR from PO
‡ Initial entry
Leverage embedded EW M
to perf orm standardized
inbound & outbound
processing with internal
movements and physical
inventory & reporting .
Leverage one system
(master data, customizing &
UX) f or reduced data -
redundancy, lean processes
with f ewer business docs
and overall simplification
Simplif ied apps f or shipping
specialist:
Ability to search f or
outbound deliveries and
returns deliveries via
object pages, including
details about header and
item data.
Optimize material f low f or
external and internal
requirements (MRP) with
system - generated solution
proposals.
Manage and track change
requests f or orders.
One single MRP if all
downstream materials are
advanced planning -
relevant.
Available to promise: new
ATP algorithm based on
HANA embedded in mass
component check in
production.
Improve percentage on -
time delivery .
Leverage just - in - time
scenarios f or inbound and
outbound.

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Real - time alerts
based on
production
bottlenecks, such
as time or
component
delays and
resource
bottlenecks
Benef it f rom
s ingle material
master
maintenance f or
ERP and SCM
relevant materials
Synchronous
commit,
consistent data
Immediate error
handling
Manage the
subcontracting
process f rom
planning to
execution and
monitoring and
integrate your
Business
Network
Integrate
external
w orkforce into
Production
Execution,
manage time,
material
handovers
Benef it f rom a
simplified
processing in
repetitive
scenarios with
mass processing
and streamlined
f inancial controls
in periodic
actions
Run your
production in
many dif f erent
f lavors to support
Kanban & Just -
in - time
sequencing f or
Inbound and
Outbound
SAP S/4HANA Manufacturing
Monitor Production Orders in an
intuitive Cockpit
Analyze & manage scrap during production
QUALITY
MANAGEMENT
Solution Capabilities:
E2E Business Process:
PRODUCTION
CONTROL
BASIC
PRODUCTION
EXECUTION
BASIC SUB -
CONTRACTIN
G
KANBAN & JIT
PROCESSING
QUALITY
ENGINEERING
QUALITY
INSPECTION
Innovation & Highlights:
Track Quality inspections intuitively
PRODUCTION
OPERATIONS
Integrated &
simplif ied solution
combining QM
and QIM
capabilities
w ith new UX f or
q - technicians, q -
engineers, q -
planners, q -
managers, q -
auditors, and
calibration
technicians
Perf orm quality
inspections
providing
inspection results
to enable timely
inf ormed release
decisions and
therefore support
ensuring product
compliance and
quality
requirements
Increase your
quality results to
new levels with
better planning,
def ection
recording and a
f lexible and
harmonized
action
management, all
supporting
standardized
complaint
process
BASIC
EXTERNAL
PROCESSING
REPETITIVE
MANUFACTU
RING
QUALITY
IMPROVEMEN
T

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Allows employees to
search and request
goods / services in a
cross - catalog
search with a
consumer - grade
user experience .
Highly integrated
requesting process
into core S/4HANA
processes and
existing master data
Supports Indirect &
Direct Procurement
with high automation,
high system support ,
and harmonized UI.
In cludes dynamic
prefilling and
provisioning of fields
as well as templates
to minimize errors. A
standard integration
into Ariba Network is
provided natively
High percentage of
automation tasks,
and additional
supporting functions
for manual
processing like
proposals displaying
available sources of
supply to overall
increase efficiency
and speed of the
sourcing process
Give buyers access
to one, integrated
system for service
purchasing to
create, display,
change, and process
purchase orders.
Support automated
and manual
processes
INVOICE PROCESSING
& ACCOUNTS
PAYABLES
INVOICE PROCESSING
& ACCOUNTS
PAYABLES
INVOICE PROCESSING
& ACCOUNTS
PAYABLES
SAP S/4HANA Procurement
Use Self Service
Requisitioning and shop in 3
steps with 1 UI
INVOICE &
PAYABLES MGMT.
Solution Capabilities:
E2E Business Process:
SELF SERVICE
REQUISITIONING
Innovation & Highlights:
Next level of Procurement via
Procurement Overview Page
OPERATIONAL
PURCHASING
COLLABORATIVE
SOURCING &
CONTRACT
MGMT.
PURCHASE ORDER
PROCESSING &
COLLABORATION
REQUIREM ENTS
PROCESSING
SERVICES
PURCHASING &
ENTRY
SOURCE
ASSIGNM ENT
OPERATIONAL
CONTRACTI
M ANAGEM ENT
INVOICE
PROCESSING &
COLLABORATION &
ACCOUNTS
PAYABLES
CLASSIFICATION,
SEGM ENTATION &
SUPPLIER
EVALUATION
SPEND VISIBILITY,
REALTIM E
REPORTING &
M ONITORING
W ith S/4HANA,
automated and
manual processes for
source assignment
to operational
demands, by using
source lists, purchase
information records
are supported
Monitor contracts in
contract w ork list
and get instant
information. Dynamic
search helps propose
possible values
already while typing
contract target
value or target
quantity updates
Classification and
Segmentation offers
logical grouping of
similar expenditure
items, such as
expenses for
advertising agency
services or IT
hardware into
Purchasing
Categories to
organize spend,
responsibilities, and
organizations
Purchasers gain role
based and quick
access to the
procurement
information they need
for analyzing
purchasing spend,
suppliers, and
contracts in real -
time
W ith Supplier
Invoice List and
Create Supplier
Invoice apps,
S/4HANA offers the
possibility to create
supplier invoices with
or w/o reference to a
purchase order, view,
and correct
inaccurate supplier
invoices directly . A
standard integration
into Ariba Network is
provided natively
Integrate your Business
Network
SUPPLIER
MGMT. &
PROCUREMENT
ANALYTICS

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SAP S/4HANA Research & Development
PRODUCT
ENGINEERING
Solution Capabilities:
E2E Business Process:
PROJECT
FINANCIALS
CONTROL
PROJECT
LOGISTICS
CONTROL
PRODUCT
DEVELOPMENT
FOUNDATION
PRODUCTION
BOM
MANAGEMENT
RECIPE /
ROUTING
MANAGEMENT
INSPECTION
PLANNING
PROJECT
CONTROL &
PRODUCT
DEVELOPMENT
Def ine w ork breakdow n
structures as basis f or
hierarchical project
accounting . Plan costs
and budgets and track
actual costs tightly
integrated with core
business processes. To
monitor project progress
and f inancial perf ormance
and enable you to avoid
cost overruns in time
Def ine project structures
comprising suitable w ork
breakdow n and netw ork
structures as basis f or
project logistics planning
and execution. Use
simplified code and
optimized data model
in line with a simplif ied
authorization concept and
initial set of CDS views f or
external consumption
Provide a product
innovation platform as
base to manage, translate,
and integrate innovations to
accelerate product design ,
m aintain discrete and
process manuf acturing
design standards, and
communicate design/recipe
updates quickly. Use new
Embedded Softw are
Management
Provide a cost - effective
production BOM
management with
comprehensive f unctionality
and synchronize master
data and product
structures continuously.
Improve transfer of design
to manuf acturing sites and
accelerate discrete or
process production ramp
up, time to volume, and
time to prof it
Def ine the routing , recipe
the bill of material , and the
production version in
relation to one another to
accelerate discrete or
process manuf acturing
production ramp - up, time to
volume and time to prof it.
Synchronize master data
and recipes continuously
Develop a closed - loop
inspection planning in
compliance with industry
standards such as ISO/TS
16949 and ISO 9000.
Implement a risk - based yet
cost - effective product and
process design and u se
f ailure mode and ef fects
analysis, as well as control
plans to recognize risks and
potential def ects at an early
stage
Manage Engineering RecordsManage Product
Structures
Use new Software
Management
Confirm Network Activity

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SAP S/4HANA Asset Management
Create Maintenance Orders
Create Measurement
Documents
Solution Capabilities:
E2E Business Process:
MAINTENANCE PLANNING
& SCHEDULING
MAINTENANCE
EXECUTION
Innovation & Highlights:
MAINTENANCE
MANAGEMENT
ƒ Plan upcoming maintenance work and
f ind the right person who can use
appropriate tools and resources to
execute maintenance activities. Handle
unplanned work requests and
incomplete inf ormation, moving it to
planned maintenance status. Gain a f ull
view of asset status to mitigate
breakdowns. Reduce maintenance
costs, while synchronizing labor,
material, equipment, and schedules
ƒ Manage proactively asset - related risks
to minimize disruption
ƒ Finding the most ef ficient maintenance
strategy
so that:
ƒ Assets are not over - maintained
ƒ Risks are under control
ƒ Value (perf ormance vs. cost)
can be maximized
ƒ Optimal asset maintenance involves
proactive - preventive or condition - based
- maintenance activities, which help
minimize equipment breakdowns. This
includes clear procedure development,
visible resource availability and access
to relevant inf ormation. On any device,
remote workers can access, transfer,
complete, and manage assigned work
orders. So asset managers and staff
increase equipment reliability and
improve asset usage as well as saf er
maintenance processes
ƒ Enable real - time insights of asset
perf ormance f or timely, relevant
decisions
ƒ Review ongoing maintenance activities
with the ability to reschedule multiple
times a day
ƒ Leverage process integration with
Predictive Maintenance and Service and
Asset Intelligence Network
Display Job List

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SAP S/4HANA Core Finance
COST
MANAGEMENT &
PROFITABILITY
ANALYIS
Solution Capabilities:
E2E Business Process:
ACCOUNTING
CLOSING
OPERATIONS
FINANCIAL
REPORTING
COST
MANAGEMENT
PRODUCT
COST MGMT.
PROFITABILITY &
COST ANALYSIS
Innovation & Highlights:
Use people centric posting cockpits for
quick overviews and fast item
processing
ACCOUNTING & CLOSING
OPERATIONS
Use one single source of
truth f or instant insight into
profitability and all ledgers
and sub - ledgers, such as :
ƒ Asset Accounting
ƒ Inventory Accounting
ƒ Accounts Payable
ƒ Accounts Receivable
ƒ Revenue & Cost
Accounting
Accelerate company close
through automation and
standardization .
Templates can be used
across multiple entities to
improve governance, share
best practices. Support
quick and ef ficient peer - to -
peer reconciliation of
intercompany balances and
invoices between group
subsidiaries
Reduce risk and cost of
real - time financial
reporting and
multidimensional data
analysis f or accounting
standards with SAP
solutions. Drill down into
f inancial statements and
source applications such as
materials management or
sales and distribution
Gain a deep understanding
of the drivers of by
achieving a holistic view
for cost management . Get
complete, accurate, real -
time inf ormation to increase
operational ef ficiency and
overall prof itability.
Minimize disruption to core
processing with role - based
access to massive amounts
of f inancial data and related
f lexible f inancial objects
Calculate Cost of Goods
Manufactured (COGM) or
Cost of Goods Sold
(COGS) as broken down by
each step of the production,
project or service process
by integrating to other
SAP applications . So the
approach to Product Cost
Management can be
approached with high
f lexibility per industry
Understand in detail the
costs & margins incurred
by your products in order
to successf ully manage
your product portf olio. W ith
immediate, role - based
insight into current margin
and f lexibility f or ad hoc
reporting and analysis, your
business users have the
support they need to
optimize decisions
Use new Cockpits for AR & AP with
charts, notes and access to all docs
Monitor your production cost in a
powerful & intuitive UI

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SAP S/4HANA Human Resources
Solution Capabilities:
E2E Business Process:
TIME SHEET
TIME
RECORDING
‡ Integrate HR information on
availability and actual w orking
times into logistical processes to
receive a holistic view on your
production cost and capacity
utilization. Leverage this HR data in
your financial reporting and
analysis for full transparency
‡ Best Practices available for the
technical enablement of SAP
S/4HANA to enable Employee
master data integration . It covers
the configuration required to store
employee and employee - related
data in SAP S/4HANA
** Additional Installation & License
S/4HANA Connectivity w ith SAP SuccessFactors **
SAP seamlessly integrates the core SAP S/4HANA capabilities with SuccessFactors as
the recommended next generation Human Resources foundation for SAP S/4HANA.

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SERVICES INITIATION
PLANNING &
SCHEDULING
SERVICE PARTS
W AREHOUSING &
FULFILLMENT
SERVICES INITIATION
PLANNING &
SCHEDULING
SERVICES INITIATION
PLANNING &
SCHEDULING
SERVICES INITIATION
PLANNING &
SCHEDULING
Provide precise
customer location and
installed - equipment
information to call
center, field service,
depot repair, and sales
staff. Maintain master
data required to perform
effective maintenance
on a piece of equipment.
Equipment Master
Record, Service - /
Maintenance Plan,
Measuring Point, Task
List, Bill of Materials
Service task lists
describes a sequence
of individual activities
to standardize recurring
work sequences and to
more effectively plan
with allocation required
resources, tools, and
materials. It helps to
reduce the service effort
when standardized work
sequences change, for
example as a result of
new legal regulations
Automatically
schedule service
commitments and
events based on time
and counter readings to
enable preventive and
predictive service
activities, based on time,
counter, condition or
risk. Prepare individual
service tasks and
allocate required
resources, tools, and
materials and plan
shutdowns
SAP S/4HANA Services
SAP S/4HANA Enterprise Management Scope for 1610 Shipment
SERVICE PARTS
MANAGEMENT
Solution Capabilities:
E2E Business Process:
TECHNICAL ASSETS,
STRUCTURE HISTORY
SERVICE
MASTER DATA
MANAGEMENT
C
SERVICE
MANAGEMENT
C
SERVICE
AGREEMENT MGT
SERVICE TASK LISTS &
CATOGUES
SERVICE
MAINTENANCE PLAN &
EVENT SCHEDULING
SERVICES INITIATION
PLANNING &
SCHEDULING
SERICE EXECUTION,
DELIVERY &
FULFILLMENT
SERVICE BILLING,
SETTLEMENT,
RETURNS, REFUNDS
OPERATIONAL
CONTRACT &
W ARRANTY MGMT.
The handling of service
agreements is common
across all industries. To
support all types of
commitments, you use:
‡6HUYLFH&RQWUDFWV
(binding contracts) that
cover details about
content, scope, conditions,
and how the services will
be performed. Such
contracts can include
contractual billing.
W arranties to commit the
service provider to certain
services.
Facilitate the optimization
of spare part stock
processing according to
usage and availability.
Improve efficiency in
parts fulfillment,
planning, procurement
and w arehousing with
integration into core
materials management
and finance functions as
well as support for
language and localization
requirements.
Tasks have to be
defined to resolve the
service issues. This
covers a portfolio of
options ranging from a
simple answ er to a
support request or
delivering a complex
service where labor and
service parts resources
are required or it can
also include returns
processing
Deliver the service in the
most efficient manner
from planning,
scheduling, parts
provisioning, execution,
and billing. Field service
organizations need to
have access to up - to -
date information about
service history and
equipment
configuration to
provide the appropriate
service
Pull billing data from
various sources to
enable accurate, timely
billing of services and
tracking of service
revenue. Quickly
generate and track bills
and invoices for services
the company provides.
Billing can be
performed
automatically resulting
in high - quality decisions
that impact the bottom
line
C
Compatibility Scope

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Soft Financial Close Anytime
Business process view
Cl os e b a t ch e s
C on s olidation b a t ch e s
Initial p eriod Cl os e & c on s olidation
R eporting on - demand
Cl os e & c on s olidationInitial p eriod
With SAP S/4HANA:
y Real - time system with key performance
indicators (KPIs) instantly refreshed
y Elimination of end - of - period batch bottlenecks
y Continuous intercompany reconciliation
y Continuous financial reporting visibility
y Profitability analysis and line - item detail
reconciliation
y Automation for routine tasks
y Full management visibility of close tasks
With traditional system:
y &ORVHDFWLYLWLHVWKDWGRQ¶WEHJLQXQWLOSHULRGHQG
y Multiple batch - run dependencies
y Batch bottlenecks that delay downstream
activities
y High error - correction efforts
y Complex issues that are postponed until after
close
y Time - pressured resolutions
y Delayed visibility into reporting
Traditional system
With SAP S/4HANA
User
interaction
Ad hoc
Traditional With SAP S/4HANA
Process excellence
User
interaction
Ad hoc

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Efficient Procurement
Business process view
Traditional System ± Buyer & Supplier Collaboration Reinvented Business Processes with SAP S/4HANA
With SAP S/4HANA:
y Full transparency of process status per PO & INV line item
y Real - tim e updates of business process inform ation
y Increased process efficiency for Buyers and Suppliers
y Short cycle tim es
y 2SHQLQJXSEXVLQHVVRSSRUWXQLWLHVIRUWKHFRP SDQ\¶VGHELW
credit accounting
y Data integrity of business inform ation across system s
y Direct exchange of business inform ation
With traditional system:
y Loose collaboration between suppliers and buyers
y Many manual interf aces
y Error - prone processes
y Inefficient collaboration due to limited transparency
y Long cycle times
y Dif f icult to identif y new business opportunities
Cycle T im e
Process excellence
x
W aiting Time
End DateStart Date
1
Purchase
Order
Purchase Order
confirm ation
Goods
Receipt
Invoice
CC - Invoice
Rem ittance Advice
Clearing
of
open
item s
2
3
4
Traditional
Strategy
New
Strategy
Rem ittance Advice
Goods Receipt
Purchase Order
Purchase Order
confirm ation
Ship Notice
Invoice
Clearing of
open item s
CC - Invoice
Invoice status
update
(Paym ent date)
Paym ent proposal
Agree on Early
paym ent
Cycle T im e
BUYER
SUPPLIER

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Real Time Inventory Management
Business process view
With SAP S/4HANA:
y Real - time inventory inf ormation, including
early error detection
y Precise where - used information per unit.
y $ELOLW\WRFKDQJHORWVL]HWR³´WKXVFDSWXULQJ
the lowest level of granularity in inventory
stock keeping
With traditional system:
y Slow update cycle leads to outdated information
y Inventory planning cannot accommodate flexible,
custom configurations
y Limited inventory visibility increases error rate and
supply shortages
Safety stock
T im e
Quantity
Reorder
point
Lea
d
tim e
Order 1
Order 2
Order 3
BOM 1
BOM 2
BOM 3
Run
inventory
updates
at night
Order 1
Order 2
Order 3
BOM 1
BOM 2
BOM 3
Ad hoc
actualization
Safety stock
T im e
Quantity
Reor
der
point
Lea
d
tim e
Traditional system W ith SAP S/4HANA
User
interaction
Ad hoc
Traditional With SAP S/4HANA
Process excellence
User
interaction
Ad hoc
Business perspective

SAP S/4 HANA
- Why S/4 HANA
- S/4 HANA Enterprise Management
- Embedded Analytics & Innovation Highlights
- SAP Fiori

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SAP S/4HANA embedded analytics
Embedded Analytics
ƒ Deliver contextualized analytics
for SAP S/4HANA embedded
within the context of work and
tailored to business needs and
roles
ƒ Consist of Virtual Data Models
based on Core Data Service
(CDS) views covering role based
operational reports for lines of
business
ƒ Come with tools for Business
Users, Pow er Users and
Developers to analyze data and
manage the lifecycle of reports
and KPIs
BUSINESS USERS
POWER USERS
SAP S/4HANA
Virtual Data Models
QUERY
DESIGNER
SAP FIORI
KPI MODELER
ABAP
FOR ECLIPSE
DEVELOPERS
FRONT
END
BACK
END
Spend of
contract
Incoming Sales
Order
«
PO Avg. Delivery
Time
Non - managed
purchasing spend
embedded analytics
SAP
SMART
BUSINESS
COCKPITS
QUERY/VIEW
BROWSER
MULTI -
DIMENSIONAL
REPORTS
ANALYTICAL
FIORI APPS

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³ Insight - to - DFWLRQ³ with SAP S/4HANA Embedded Analytics
OLTP
Traditional:
OLTP & OLAP Separate
>48 Hours
10:00 AM 10:00 AM
OLTP + OLAP
in SAP HANA
10:00:00 AM 10:00:00 AM
Immediate
Instant Insight to Action on Live Data
>48+hr Old Data
Aggregate
ETL
Multiple Data Sources
OLAP
Replication
Replication
Replication
Application
101010010101
001001010011
0101101101110
100100010011
101010010101
001001010011
0101101101110
100100010011
SAP S/4HANA
Decisions and Actions on Old Data
Multiple Data
Sources

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Imagine if you had contextualized insights at your fingertips
Procurement: Material order entry
Enter material order
Check budget overview
Check average
supplier delivery
performance
Review detail report
Purchasing
manager
Choose best supplier
and
complete material
order entry
Start
transaction
Complete
transaction
All on one screen
9 Faster customer delivery
9 Larger average deal size
9 Fewer warehouse stock outs
Analyze and predict

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SAP S/4HANA
Real time analytics architecture
Atomic
Pre - defined
Instantaneous
HANA Database Layer
SQL - Runtime - Views on Physical Tables
ABAP Layer
Virtual Data Model, based on Core Data Services (CDS)
Analytical Apps and BI
Clients
e.g. SAP BusinessObjects
SAP S/4HANA Application
Hybrid Transactional and
Analytical Applications
e.g. SAP Smart Business
.3,¶V
‡ Full ABAP Lifecycle Integration
‡ Supporting ERP authorizations
‡ Supporting ERP hierarchies
‡ Part of the general Extensibility concept
‡ Supporting more business cases
DQDO\WLFVVHDUFK IDFWVKHHWVSODQQLQJ«
‡ No latency
‡ No data duplication
‡ Ready - to - use content
‡ Integration scenarios with SAP BW
Analytical Engine*
*generating Transient BEx Queries

261
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SAP S/4HANA 1610
Innovation Highlights for Analytics
Process / Analytics Innovations
» Customer edit delivered KPIs
» Custom CDS view app
» View Browser to show all delivered CDS views
» Content so far:
» more than 8.900 views created
» (PEHGGHG$QDO\WLFDO$SSOLFDWLRQVLQFO.3,µVFUHDWHG
Integration highlights
» Smart Business and Analysis Path Framework Integration

262
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Featured new and enhanced tools and functionality
View Brow ser
Custom CDS ViewKPI Modelling Apps
Query Builder
Analysis Path
Multidimensional
Reporting Client

263
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SAP S/4HANA embedded analytics + SAP BW on SAP HANA or SAP BW/4HANA
Comprehensive operational + historical analytics and planning powered by SAP HANA
All analytics requirements fulfilled w ith one unified solution
Data Integration Scenarios are possible in multiple hybrid system setups
y Strategic and tactical
y Integration, harmonization,
cross - system consistency
y Consumption
y Planning Platform
y Multi - sourced data
y Preconfigured content
y Data lifecycle
y Data governance
y Complete analytical suite
y Operational data
y Real - time
y Lightweight modeling and
consumption
y Extensible
y Uniform
y Basis for multiple embedded
use cases
y Model reuse in analytical
applications
y Lightweight planning solutions
SAP S/4HANA embedded analytics
M ulti - channel Unified User Experience
SAP S/4HANA
(incl. Virtual Data Model)
SAP NetW eaver
New SAP Apps
Partner
Apps
SAP HANA PLATFORM
SAP BW
Database Services (include SAP HANA Views)
Synchronizations Services
Application Services
Additional positioning blog:
http://scn.sap.com/community/s4hana/blog/2016/04/07/
the - end - of - sap - business - warehouse - in - the - context - of -
sap - s4hana - is - not - in - sight

SAP S/4 HANA
- Why S/4 HANA
- S/4 HANA Enterprise Management
- Embedded Analytics & Innovation Highlights
- SAP Fiori

265
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SAP S/4HANA: What does it look like?
SAP Fiori
Single entry point
Domain specific infos and actions
Enter details and explore in depth
The SAP Fiori launchpad will be the
single entry point to access all apps
Users quickly get an overview of what needs
their attention with Overview Pages , List
Reports, and Work Lists , can trigger quick
actions or drill dow n to the next level of detail
Key and differentiating use cases will be re -
imagined with the SAP Fiori user experience
All ³FODVVLF´WUDQVDFWLRQV will have the SAP Fiori
visual theme
Native iOS
mobile
experience for
high - impact
scenarios

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SAP S/4HANA 1610
Capabilities highlights for the user experience of SAP S/4HANA ? SAP Fiori 2.0*
Integrated
Quality
M anagement
Industry to
Core
Portfolio and
Project
M anagement
Extended
W arehouse
M anagement
Production
planning and
detailed
scheduling
advanced
Available to
Promise
Embedded
Software in
Product
Development
Efficient
Procurement
Entire Finance
Scope in
SAP S/4HANA
The User
Experience of
SAP S/4HANA
Real time
Inventory
M anagement&
M aterial
Valuation
Accelerated
M aterial
Requirements
Planning
Effective
Order
M anagement &
Billing
Me Area Notification Area
** Some aspects shown are future direction
Workspace
User experience of SAP S/4HANA – SAP Fiori 2.0**
* D oes not reflect licensing

267
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SAP Fiori analytics
Concepts and Designs
Analytical List PageOverview Page Object Page
» Light - weight analytical capabilities in context
» KPIs and data visualization as part of the business process
» Visual filtering and intuitive selection based on charts
» Reach - out from the transaction into powerful analytical tools
transferring available context
Cloud for Analytics

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SAP S/4HANA
Principles & Elements of SAP FIORI Launchpad
Single Entry Point
for all User Activities
via Fiori Launchpad
- any device
Group tiles for
personalized
content organization
News and feeds to
enhance
collaboration
Realtime .3,¶VZLWK
color coding alerts user
for any overdue, new or
immediate actions
Dynamic charts to
provide high level,
real - time overview
Roles fully supported by
Backend authorizations
managed on Hana
Search across and
within apps to get
immediate answers
SAP Jam integrated to
provide instant
feedback on
notifications and group
activity

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SAP Fiori apps reference library ± ³$)LRULDSSDERXW)LRULDSSV´
± Repository of all released apps and their versions
± Contains app descriptions with screenshots
± Implementation details per app
± Aggregated view of selected apps regarding
“ Installation requirements
“ Configuration information
± Direct access to related resources:
documentation, Product Availability Matrix ,
Innovation Discovery and Maintenance Planner
www.sap.com/fiori - apps - library

270
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SAP Fiori implementation
Selection of apps in SAP Fiori apps reference library
270

Real Customer Use Cases

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Course Outline
SAP S/4HANA status before 1610 release on October 31st
333+
Live Customers
4,100+
Licensed Customers
1,470+
Active Customer Projects
In all 25 industries & 77 countries

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SAP S/4HANA 1610
Country versions
Brazil
United States
Canada
Chile
Venezuela
Mexico
Peru
Argentina
Colombia
United Arab Emirates
France
Netherlands
Belgium
Great Britain
Germany
Luxembourg
Sw itzerland
Croatia
Romania
Poland
Norw ay
Bulgaria
Austria
Greece
Denmark
Slovakia
Ukraine
Ireland
Italy
Israel
Turkey
Finland
Lithuania
Spain
Sw eden
Russia
Portugal
Czech Rep
Estonia
Latvia
Serbia
Hungary
Oman
Saudi Arabia
South Africa
Egypt
Qatar
Kuw ait
Slovenia
Singapore
Philippines
South Korea
Taiw an
Thailand
Hong Kong
Malaysia
PR China
Australia
Japan
India
Kazakhstan
Indonesia
New Zealand

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SAP S/4HANA ± 5,800+ Customers*
Reference examples per industry
M ARKETING COM MERCE
HUM AN RESOURCES M ANUFACTURING SUPPLY CHAIN
SALES
FINANCE
SERVICE
SOURCING & PROCUREM ENT
ASSET M ANAGEM ENT RESEARCH & DEVELOPM ENT
HIGHER EDUCATION & RESEARCH
SPORTS, M EDIA & ENTERTAINM ENT
DISCRETE M ANUFACTURING M ILL & M ININGSERVICES
FINANCIAL SERVICES
HEALTHCARE CONSUM ER
TELCO & UTILITIES
*as announced during SAP 2016 earnings on January 24, 2017

Summary

276
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Course Summary
You should now be able to:
9 Introduce SAP Digital Core concept
9 Introduce key features of S/4 HANA
9 Introduce the comparison of traditional ERP and S/4HANA
9 Sketch out the components of S/4HANA

Thank you.

PUBLIC
SAP Digital Business Service China
Hands on
S/4 HANA - Simple Finance

279
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Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

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ƒ Story1
± Exercise 1: Display Financial Statement
ƒ Story2
± Exercise 2: Overdue Receivable
Agenda

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Course Goals
This course will prepare you to u
‡ Display Financial statement
‡ Deal with Overdue Receivable and Push Cash Flow

Story 1

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Story 1
Story :Emma is a financial manager accountable for the accounting
operations of the company, which includes, but is not limited to the
period financial reports such as the Balance Sheet and the Profit & Loss
(P&L). Before releasing the financial reports ,Emma reviews them
looking for abnormalities, drastic changes, to name a few.
In the next few minutes you will see how easy SAP S/4HANA Cloud
makes this with quick access to the real - time financials, the ability to
search and drill down into the transactions that make - up the financial
statements.
Financial
Manager
*Screenshots shown are for dem onstration purposes only and are not final product com mitments

Exercise 1
Display Financial Statement

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Display Financial Statement
Explanation
1. Click drop down list button.
2. Click Finance.

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Display Financial Statement
Explanation
3. Click title.
DQG,QSXWLQWR³&RPSDQ\
&RGH´

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Display Financial Statement
Explanation
6. Click the drop down list which
Company Code is 1710.
7 and 8. Input 1720 into Statement
Version.

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Display Financial Statement
Explanation
9. Click drop down list which version is
1720.
10. Click Go button.
Note : With this app, can display
balance sheets and profit and loss
statements for various companies by
entering the necessary selection
criteria.
These reports are generated on the fly
by analyzing all the relevant line items,
as controller wants to view Expense
details, hence profit and loss tab has
been selected.

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Display Financial Statement
Explanation
11. Click drop down list button.
12. Click input field.

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Display Financial Statement
Explanation
13 and14. Fill in search key word
³WUDYHO´DQGFOLFNVHDUFKEXWWRQ
Note : As the list is huge, Controller
can use the search criteria for the
relevant items for analyzing. For
example, here he would like to search
the Travel expenses.

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Display Financial Statement
Explanation
15. Click the amount 58.52.
16. Click

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Display Financial Statement
Explanation
17. Click the first item Journal Entry
QXPEHU³´
&OLFN³-RXUQDO(QWU\$QDO\]HU´

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Display Financial Statement
Explanation
DQGLQSXW³FXVWRPHU´LQWR
Dimensions and click search button.
Note : With this app you can analyze
journal entries posted in a selected
period. You can see Journal Entry by
Company Code, Fiscal Year/Period.
There are also numerous other
attributes that can be added as rows
or columns in this report. You can find
them by scrolling or searching in the
Navigation Panel.
You can also see the document posted
to each G/L account
Controller can review the Journal Entry
Analyzer.
Controller can add the dimension for
example here adding customer in the
dimension.

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Display Financial Statement
Explanation
&OLFN³FXVWRPHU´
&OLFN³1DYLJDWLRQ3DQHO´
Note UHYLHZWKHµ-RXUQDO(QWU\
$QDO\]HU ¶UHSRUW DORQJZLWKWKH
DGGLWLRQDOGLPHQVLRQ³&XVWRPHU´

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Display Financial Statement
Explanation
&OLFN³+RPH´

Story 2

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Scenario
Financial
Manager
Story :As the Financial Manger Emma have been receiving pressure that our cash
flows are way too low and that Emma need to get them up as soon as possible. So when
ORRNLQJ DWOLYHWLOHV,QRWLFHWKDWRIRXUUHFHLYDEOHVDUHRYHUGXH 7KDW¶VKXJH
*Screenshots shown are for dem onstration purposes only and are not final product com mitments
What is Accounts Receivable (A/R) :
1. Accounts receivable accountants are responsible for collecting outstanding invoices in the
timeliest manner possible. SAP S/4HANA Cloud helps them proactively manage outstanding
balances with easy to understand analytics that show the breakdown of how late they are -
with the ability to easily drill down to see which customers make up that balance.
2. Additionally, SAP empowers the accounts receivable person to see which invoices, credits
and chargebacks make up that balance, which they can quickly share with the customer.
3. SAP S/4HANA Cloud gives A/R accountants and managers the ability to gain insight and
act upon to help reduce Dales Sales Outstanding (DSO).
Let me walk you through a quick example of how you could manage your A/R with SAP
S/4HANA Cloud.

Exercise 2
Overdue Receivable

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Display Financial Statement
Explanation
1. Click drop down list button.
2. Click Finance.

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Overdue Receivable
Explanation
3. Click the title.
4. Click drop down list button.
Note : We need to figure out which
accounts have not paid us yet and
close them out immediately.

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Overdue Receivable
Explanation
5. Click By Customer (Top 10
5HFHLYDEOHV&KDUW´

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Overdue Receivable
Explanation
6. Click share button
7. Click Send Email
Note : I need the accounts receivable
team to start getting these accounts
closed as soon as possible, closing
even a few of these accounts will keep
us from having to take more desperate
measures to bring back our cash flow.

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Overdue Receivable
Explanation
8,9 and 10 . Input e - mail address ,
subject and send the e - mail .
Note : /HW¶VLQIRUPWKH accountant that
this is of utmost importance and send
them a link to graph that I am referring
to.

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Overdue Receivable
Explanation
11.Click button
12. Click button
Note : We want to look at the overdue
items by line item. This way we can
see exactly what transactions are of
the highest priority.

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Overdue Receivable
Explanation
13. Click column Amount( CoCo Cur).
&OLFNGURSGRZQEXWWRQ ³6RUW
'HVFHQGLQJ´

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Overdue Receivable
Explanation
15. Click second item which Customer
is USCU_S06
&OLFN³3URFHVV5HFHLYDEOHV´
Note : The first line item we see is a
ODUJHQXPEHU WKDWLVRYHUGXHVROHW¶V
click on the customer
code USCU_S06 and learn a little
more about who they are.
Here we get a quick snippet of
customer information, and looking at
the name we immediately recognize
that it is our overdue receivable leader
from the previous graph, Hub &
Spokes Inc. Recognizing this as the
try and take care of this as soon as
SRVVLEOH0HDQLQJOHW¶VSURFHVVWKLV
receivable.

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Overdue Receivable
Explanation
18. Click Edit Contact Person

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Overdue Receivable
Explanation
19 and 20. Change Contact name .

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Overdue Receivable
Explanation
21 and 22. input e - mail address.

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Overdue Receivable
Explanation
23. Click OK
24. Click Create Correspondence.
Note : Along with the invoice we should
prepare a list of all Open list items so
he can remind them what else is
due. For this we make sure that the
Correspondence is set to Open Item
List

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Overdue Receivable
Explanation
25. Click button
26. Click the date.

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Overdue Receivable
Explanation
27. Click Preview button
Note : Here we can see the official line
item break down for the outstanding
payments, we can save this to send to
the customer.
By leveraging the Sales rep., we were
able to close out the smith industries
receivable. Raising company cash
flows, and getting our sales reps their
compensation.

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Overdue Receivable
Explanation
28. Click Home button

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Course Summary
You should now be able to:
9 Display Finance Statement
9 Deal with Overdue Receivable and Push Cash Flow

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Use Case : Walmart
Click here to play the video

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Use Case :Machine Learning and Simple Finance
Click here to play the video

Thank you.

PUBLIC
SAP Digital Business Service China
Hands on
S/4 HANA - Simple Logistics

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Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

320
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
ƒ Story1
± Exercise 1: Procurement
ƒ Story2
± Exercise 2: Sales Order Fulfillment
Agenda

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Course Goals
This course will prepare you to u
‡ Procurement
‡ Sales Order Fulfillment

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Sales Order
Entry
‡ This demo starts with creating a rush order for Battery, which is from a priority customer and needs to
be delivered asap.
‡ Immediately after creating the sales order, the Sales rep gets to know that the order is only partially
confirmed. Immediately inform the material planner about unconfirmed quantities.
MRP & Material
Coverage
‡ The material planner checks the system and triggers MRP in real time. The MRP creates a planned
order and also dependent demand for the components.
‡ While checking the planned order, the material planners realizes that there is a shortage for a specific
component quantity and the system is already proposing solutions to manage the shortage.
‡ The material planner creates a purchase requisition for the component with a specific supplier
Procurement
‡ The purchaser see open purchase requisitions and decides to convert it into a purchase order.
However since the component is needed immediately, check supplier performance to ensure that the
supplier with best overall score is chosen.
‡ satisfied with the supplier already assigned and therefore convert the purchase requisition to purchase
order.
‡ The warehouse clerk post the GR for the purchase order as soon as material arrives.
Business Flow

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Production
Execution
‡ The production supervisor then triggers the production by converting and releasing the planned order
into production order.
‡ After the last production operation is confirmed, the GR for production order is automatically posted
and component quantities are back flushed .
Sales Order
Fulfillment
‡ The sales rep checks the stock overview and sees the updated stock.
‡ She confirms the sales order now, resolve all other open issues with the sales order, creates the
delivery, posts the goods issue, and at the end creates an invoice.
‡ This finishes the logistics process.
Profitability
analysis
‡ Since this was, a rush order from a priority customer and it was delivered on time. The finance
manager wants to check if it was profitable, so he opens the profitability dashboard, sees the overall
profitability, and then drills down to check the sales order specific profitability. The sales order was
indeed profitable
Business Flow

Story 1

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Story 1 Procurement
My name is Emma work at toy company Hypercom purchasing department that
are responsible for buying and have contracts with suppliers. company needs
to buy batteries for production and Emma and her colleagues have created
rush orders and the material planner finished planning order , The material
planner creates a purchase requisition for the component with a specific
supplier.
As the purchase requisitions have been approved and what she need to do is
to convert it into a purchase order. However since these batteries are needed
immediately, check supplier performance to ensure that the supplier with best
overall score is chosen.
*Screenshots shown are for dem onstration purposes only and are not final product com mitments

Exercise 1
Procurement

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Procurement
Explanation
1. Click here .
2. Click
Note :We are responsible for buying.
We have contracts with our suppliers
and we try to keep a diversified
supplier base so that we do not have
disruptions in production. /HW¶VWDNHD
look at the Procurement Overview
page.

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Procurement
Explanation
3. )LOO³%DWWHU\´ LQWRWKHILHOG
4. Click the first item which material is
³0= - TG - $´
Note : Now, all the data on the
overview page is filtered using the
chosen material "Lithium Ion Battery
400 Wh /HW¶VVWDUW RQWKHULJKWVLGH -
we see an Urgent Purchase requisition
for the battery. /HW¶VWDNHDORRNDQG
resolve the issue so we can get the
batteries we need. On the right side,
we also see the supplier performance
for the two suppliers, which are
available for the battery. Recognize,
that "Electronics Supply Inc." has the
better overall score.

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Procurement
Explanation
5. Click
&OLFN³6RXUFHV´
Note : A decision needs to be made to
select the supplier for this purchase
requisition. We can see the 2 suppliers
we need to choose from - we have
contracts with both. /HW¶VJRDKHDGDQG
pick Electronics Supply - we already saw
on the overview page, that this one has
the better overall score. The purchase
requisition will then be converted into a
PO.

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Procurement
Explanation
7. Click the first one.

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Procurement
Explanation
8. Click back button .
'HOHWHVHDUFKFROXPQ³0DWHULDO´
'HOHWHVHDUFKFROXPQ³3ODQW´

332
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Procurement
Explanation
11 and 12 . Fill in 3RODULVWR³6XSSOLHU´
13. Select the first item which supplier
LV³8668 - 96)´
Note : We see, that the Purchasing
Spend trend has changed and also,
the overall Supplier Performance is
not that good. So, let's check the
Supplier Evaluation Trend to see, if we
can figure out what are the main
points we should discuss with Polaris
representatives.

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Procurement
Explanation
&OLFN³(YDOXDWLRQ7UHQG´
15. Click Home button .
Note : Here, we can see the Overall
Score drilled down into details in
regards to Price Variance, Time
Variance and Quantity Variance for
Polaris. Seems they not stick to the
agreed upon prices very well and also
Quantity Variance has to be improved.
So, let's keep this in mind when
discussing with them.

Story 2

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Story 2 S ales Order Fulfillment
Lilly works at a company that selling batteries , Recently her company is doing a
business with Hypercom selling Batteries to this toy company .
The production had been triggered and planned order had been converted and
released into production order. Production order was posted and batteries
quantities were flushed .
What need Lilly do is to confirm the sales order, resolve all other open issues with
the sales order.
*Screenshots shown are for dem onstration purposes only and are not final product com mitments

Exercise 2
Sales Order Fulfillment

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Sales Order Fulfillment
Explanation
1. Click here .
2. Click blue point
Note : Here you see the sales order
issues of the customers we are
responsible for on one single chart.
We have 3 dimensions Issues in Total,
when is the next action and the value
of the issues. We could now deep dive
into the situation by filtering and
selecting. I will directly go to one
customer and see the relevant details
and go deeper.

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Sales Order Fulfillment
Explanation
&OLFN³,VVXH´
&OLFNWKHVHFRQG³%LOOLQJ%ORFNLQ
6DOHV2UGHUV6´

339
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Sales Order Fulfillment
Explanation
&OLFN³2SHQ´ %XWWRQ
&OLFN³5HVROYH6DOHV2UGHU ,VVXHV´

340
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Sales Order Fulfillment
Explanation
7. Click the third one which Sales
Order is 246.
Note : Here, we see all Sales Orders
which are blocked for billing with
additional data like "Net Order Value"
or "Delivery Date". So, we want to
work on the issues and see, if we can
solve it. So let's select one Sales
Order.
&OLFNWKHVHFRQGLWHP³%ORFNHGIRU
LQYRLFLQJ´
Note : For this Sales Order, the
payment terms have to be checked -
this is the blocking reason. As we
know that the company has to pay
immediately, we not only can analyze
the issue here, we also can directly
solve it changing the payment terms.
&OLFN³(GLW3D\PHQW7HUPV´

341
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Sales Order Fulfillment
Explanation
&OLFN³3D\ ,PPHGLDWHO\ ZR
'HGXFWLRQ´
&OLFN³5HPRYH%LOOLQJ%ORFN´
Note : After we changed the payment
terms, this Sales Order is now ready
for billing. Let's remove the billing
block directly in the app.

342
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Sales Order Fulfillment
Explanation
12. Click back button .
Note : Here in the overview we can
see, that the analytics is updated real -
time as the count for the "Billing Block
in Sales Orders" was reduced by
1.then click back button.
13. Click home button .

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Course Summary
You should now be able to:
9 Know Procurement Overview and do purchase procurement
9 Resolve issues with the sales order

344
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Use Case : BMW
Click here to play the video

Thank you.

PUBLIC
Lecture: Agile Implementation
Introduction of SAP Activate and Solution Manager
SAP Digital Business Service China

347
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

348
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
ƒ SAP Activate methodology
± SAP Activate methodology overview
± SAP Activate Key Characteristics
ƒ SAP Solution Manager 7.2
± Solution Manager 7.2 overview
± Solution Manager 7.2 Functional Areas
± Solution Manager 7.2 - Optimal for Digital Business
Transformation
Agenda
7.2

349
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Goals
This course will prepare you to u
y Understand the SAP Activate methodology Guiding Principles
y Get an overview of what Solution Manager 7.2 supports
y List the function areas of Solution Manager 7.2
y Describe how Solution Manager 7.2 can help on Digital Business
Transformation

SAP Activate methodology

351
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP Activate methodology overview
Next generation agile methodology that drives customer success
The SAP Activate innovation adoption framework is a unique combination of best practices, methodology, and guided
configuration to help customers and partners implement the SAP S/4HANA suite.
Objectives
‡ Plan, manage, and deliver implementation projects quickly and easily
‡ Simplify modifications and upgrades, including testing
‡ Take advantage of industry - specific functionality by integrating with third - party solutions
Solution
‡ Ready - to - run business processes, optimized for SAP S/4HANA
‡ Set of tools for an assisted implementation, covering everything from the initial implementation of a project to running in a
production environment and beyond
‡ Consistent, guided approach for any implementation scenario based on best practices, whether on premise, cloud, or hybrid
Benefits
‡ Accelerated time to value
‡ Lower total cost of ownership
‡ Less service intensive implementation projects

352
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP Activate for managed cloud and on - premise
Iterative implementation with frequent validations
Jump - start project w ith
pre - assembled
solution
Identify & validate
delta requirements
and gaps
Build customer
solution in short, time -
boxed sprints
Safeguard build and
run w ith ICC**, OCC**
and MCC**
Prepare
Pre -
Assembly
Solution Scope
and Value
Determination
Initial
Roadmap and
Approach
Explore
Delta
Design
Deploy
Technical and
System testing
Realize
Baseline Build
Sprint Execution
Solution Validation including
Gap Validation**
Prioritize Backlog
Release and
Sprint Plan
Integration Testing
Value Audits
Setup Operations
or OCC**
Organizational
and Production
Readiness
Cutover
Support after
Go - Live
Run
Operations
Control Center
Application
Lifecycle
Management
Value
Management
** Deliverables, milestones and activities are only applicable in SAP Premium Engagements.

353
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Start with SAP Best Practices
,QQRYDWLRQDGRSWLRQPDGHVLPSOHZLWK6$3%HVW3UDFWLFHVŒDQG6$35DSLG'HSOR\PHQW6ROXWLRQV
ƒ Get a jump - start for your implementations with
6$3%HVW3UDFWLFHVŒ
ƒ Deploy SAP innovations fast, simple and flexible
ƒ 8VH6$3¶VW ested and proven methodology with
prescriptive guidelines
ƒ Leverage preconfigured business content
ƒ Protect your on - premise investments with extensions
to the Cloud
ƒ Move up on the path to the cloud from pre - assembled
trials to productive use
Fast time to value
Predictable results
Simple on - boarding
to cloud

354
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Agile Build: Use of SCRUM - based approach to build solutions
Sprint BacklogSprint Retrospective
Sprint Execution
Sprint Planning Meeting
Sprint Review Meeting
Scrum Process
Recurring Cycle
Design
Scope
Product
Backlog
Usable
Software

355
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Agile Build: Iterative Realize Phase
Agile Release
Business Priority
Product Backlog
Must
Should
Could
Would
Priority
days
16
15
14
13
12
11
10
09
08
07
06
05
04
03
02
01
4
5
1
8
2
7
3
4
2
2
4
3
3
6
4
5
Realize« Explore
Time
Iterations & Demos
Sign - Off
( Organization
readiness )
Sprint 1
Sprint 2
Firm - up
Sprint
Unit
Unit
Epic / Scenario
Sprint 3
Sprint 4
Firm - up
Sprint
Epic / Scenario
Integratio
n Test
User
Acceptance
Unit
Unit
String
String

Solution Manager 7.2

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SAP Solution Manager 7.2 is fantastic for Build SAP
SAP Solution Manager 7.2 supports outcome - based delivery .
Automated
‡Tiresome and error-prone labor is
eliminated
‡Automated real-time dashboards replace
spreadsheets
‡Centralized automated status of all projects
worldwide
Jumpstart
‡Predict and realize business value
‡Standardized project plans and services
‡Best-practice processes and pre-
configuration
‡Always up-to-date with One Content Cloud
Agile
‡Build what the business needs, when they
need it
‡Continuous feedback loops with the
business
‡Incremental delivery of solution
‡Agile Release Train
Out-Task
‡Package and distribute work
‡Centralized orchestration of distributed delivery
teams
‡Track solution readiness against due dates
‡Collaboration and quality assurance with SAP

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SAP Solution Manager 7.2 in a nutshell
IncidentMonitor
Detect to
correct
Problem Optimize
Portfolio Management Project Management
Portfolio to
Project
Demand Design DEV Test Deploy
Requirement to
Deploy
Service Request
Service
Catalogue
Request to
Fulfill
Service
Fulfillment
SAP Solution Manager 7.2 delivers 4 key value scenarios
Value scenarios - Life - cycle view

359
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Change
SAP Solution Manager Integration Model
Key Documents of the Four Value Chains 1/2
Portfolio Management Project Management
Portfolio to Project
Demand Design Dev Test Deploy
Requirement to Deploy
Initiative
Investment
B ucket
Portfolio
Item
Project IssueRisk
Requirement
Work
Package
IT
Requirement
Work Item Test Case
Test Plan
Release
Defect

360
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Service RequestService Catalogue
Request to Fulfill
Service Fulfillment
SAP Solution Manager Integration Model
Key Documents of the Four Value Chains 2/2
Request for
Change
Guided
Procedure
Incident
Problem
Alert
Incident
Analysis
Bus. Proc.
Analytics
IncidentMonitor
Detect to correct
Problem Optimize
Service
Request
Service
Catalogue
Guided
Procedure
Task

361
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP Solution Manager 7.2
Functional Areas
Project
Manage
Custom
Code
Manage
Change
Control
Manage
Landscape
Manage
IT Service
Manage
Data Volume
Manage
Application
Operations
Process
Manage
Business
Process
Operations
Test
Suite
Detect to
Correct
Portfolio to
Project
Requirement
to Deploy
Request to
Fulfill

362
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP Solution Manager 7.2
Optimal for Your Digital Business Transformation
Launchpad, Apps
and Dashboards
One Process Landscape
for Business and IT
Transparent
requirements to deploy
On - Premise, Hybrid
and Cloud Solutions
DIGITAL BUSINESS
SAP S/4HANA
and SAP customer
solutions
SAP Solution Manager
on SAP HANA

363
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP Solution Manager 7.2
Optimal for Your Digital Business Transformation
Launchpad, Apps
and Dashboards
Transparent
requirements to deploy
On - Premise, Hybrid
and Cloud Solutions
SAP Solution Manager
on SAP HANA
DIGITAL BUSINESS
SAP S/4HANA
Digital Industries
One Process Landscape
for Business and IT

364
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Launchpad, Apps & Dashboards
Providing the ultimate user experience
SAP Solution Manager Launchpad offers role - based access
to all relevant applications and Work Centers
SAPUI5 / Fiori apps for key business - facing UIs and mobile
applications.
Vital SAP Solution Manager UIs are revamped incrementally
XVLQJ6$38,)LRULEDVHGRQFXVWRPHUV¶XVDJHDQG
demand.
All Flash - based UIs for Run SAP applications and the existing
SAP Solution Manager dashboards are converted to SAPUI5.
Browsers supported by the SAP Business Suite are also
supported by SAP Solution Manager.
SAP Solution Manager 7.2 follow s the SAP Business Suite Strategy.

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Launchpad, Apps & Dashboards
Analytics Overview
Custom, Best - Practice DashboardsCross - Application Dashboards
Application - specific Dashboards
Customer creates individual
dashboards based on
predefined models in minutes.
Ideal for jumpstarting OCCs.
Customer picks and chooses
KPIs from a KPI catalogue to
create tiles on individual
dashboards.
Customer consumes
dashboards per application
as they are.

366
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP Solution Manager 7.2
Optimal for Your Digital Business Transformation
Launchpad, Apps
and Dashboards
Transparent
requirements to deploy
On - Premise, Hybrid
and Cloud Solutions
SAP Solution Manager
on SAP HANA
DIGITAL BUSINESS
SAP S/4HANA
Digital Industries
One Process Landscape
for Business and IT

367
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
One Process Landscape for Business and IT
Big Picture
State - of - the - Art Business Process Modeling in SAP Solution Manager 7.2
covers the w hole lifecycle of a solution.
Design
To - be processes &
requirements
Build
Agile requirements
fulfillment
Run
Continuous improvement
based on real usage
Digital
Transformation

368
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
One Process Landscape for Business and IT
Process Management in SAP Solution Manager
ƒ SAP Solution Manager solution
documentation
± Web - based documentation experience
± Integrated BPMN process editor
± Multi - level hierarchies ( more than three )
± Processes assembled from re - use libraries
± Processes are validated and optimized continuously
based on real usage
ƒ Integrated process experience
± Requirements Management
± IT Project and Portfolio Management integration
± Change and Request Management integration
± Test Management integration
± Business Process Monitoring integration
Today, customers are challenged w ith synchronizing business models and processes with
IT solution documentation across build and run.
Integrated graphical BPMN process editor

369
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
One Process Landscape for Business and IT
New Business Process Monitoring application
See the status of the last data collection for your
business processes in a simplified tabular display,
optionally per step or interface.
In addition, you can see a graphical
representation of your business process flow.
This makes use of the new process graphic from
the solution documentation.
From both screens you can navigate to the details
of the collected metrics (e.g. last measured value
or detail list).
Process Management and Process Monitoring share the same foundation!

370
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP Solution Manager 7.2
Optimal for Your Digital Business Transformation
Launchpad, Apps
and Dashboards
On - Premise, Hybrid
and Cloud Solutions
SAP Solution Manager
on SAP HANA
Transparent
requirements to deploy
DIGITAL BUSINESS
SAP S/4HANA
Digital Industries
One Process Landscape
for Business and IT

371
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Transparent Requirements - to - Deploy
Outcome based delivery - constant feedback loops with the business
Value added by methodology & tools
± Automated visibility of solution readiness against
due dates, with integrated risk management
± Management of distributed development teams
± Agile release and software engineering with
optional JIRA integration
± Automated test planning, change & release
management to support continuous delivery &
integration and DevOps
± Full integration of demand, project, process,
change, release and test management
Ready - to - run, and integrated, tool - supported methodology to manage
requirements and softw are development in large, agile projects.

372
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP Solution Manager 7.2
Optimal for Your Digital Business Transformation
Launchpad, Apps
and Dashboards
Transparent
requirements to deploy
On - Premise, Hybrid
and Cloud Solutions
SAP Solution Manager
on SAP HANA
DIGITAL BUSINESS
SAP S/4HANA
Digital Industries
One Process Landscape
for Business and IT

373
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
On - Premise, Hybrid and Cloud Solutions
There Is More Cloud Than You Think!
± Build, Deploy, and Run for SAP
cloud products
± Same level of standards for
cloud as on - premise
± Cloud Appliance Library
± SAP Solution Manager as a
Managed Service
± Maintenance Planner
± KPI Catalogue
± Roadmap Viewer
± SAP S/4HANA Readiness
Check
± Best Practices
SAP Solution Manager
for Cloud
SAP Solution Manager
with Cloud
SAP Solution Manager
on Cloud

374
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP Solution Manager 7.2
Optimal for Your Digital Business Transformation
Launchpad, Apps
and Dashboards
Transparent
requirements to deploy
On - Premise, Hybrid
and Cloud Solutions
SAP Solution Manager
on SAP HANA
DIGITAL BUSINESS
SAP S/4HANA
Digital Industries
One Process Landscape
for Business and IT

375
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP Solution Manager on SAP HANA
More value through in - memory technology
ƒ Performance increase
± Drastically faster text search functionality opens new opportunities e.g. to work with documents,
service reports, ITSM tickets
ƒ SAP HANA only strategy
± If SAP HANA is the only platform at your company, SAP Solution Manager 7.2 is your perfect
lifecycle management platform
ƒ SAP Solution Manager as a door opener for SAP HANA
± First system in a general plan to migrate to SAP HANA and become familiar with it
± Preparation of SAP HANA operations
Why choose SAP Solution Manager 7.2 on SAP HANA?
SAP HANA

376
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Digital Business
Use SAP Activate for SAP S/4HANA for delta scoping
1. You can download this content into your
SAP Solution Manager
2. From the diagram, you can jump into
SAP FIORI apps in a pre - activated
SAP S/4HANA trial system
3. Execute show and tell of the SAP
S/4HANA innovations hands - on
4. Document requirements as a result of
this fit/gap analysis
SAP Activate provides SAP S/4HANA best - practice process content that consists of process
diagrams, documentation, and configuration.
1
2
3
4
SAP S/4HANA
On - Premise Edition

377
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Summary
You should now be able to:
9 Understand the SAP Activate methodology Guiding Principles
9 Introduce the steps of SAP Activate
9 Introduce the key values of Solution Manager 7.2
9 Sketch out the 6ROXWLRQ0DQDJHU ¶V Function areas &
Application scenarios

Thank you.

PUBLIC
SAP Digital Business Service China
Hands on
End - to - End Defect to Fix process (Solution Manager 7.2)

380
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

381
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
ƒ Scenario
ƒ Exercises
± Create Process Diagram
± Incident Handling
± Change Processing
Agenda

382
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Goals
This course will prepare you to u
‡ Create Process Diagram
‡ Create / Dispatch / Process an incident
‡ Request a change / Process a change

Scenario

384
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Scenario
Emma discovered an
issue while creating, she
UHTXLUHVH[SHUW¶VKHOS
Create Process
diagram
Issue Discovered Issue needs to be fixed
B usiness
Consultant
Expert found a bug
after investigating, he
creates a request for
change to fix the bug
immediately
*Screenshots shown are for dem onstration purposes only and are not final product com mitments
Boss needs a
comprehensive
order - to - cash
process
Emma create a visible
order - to - cash process
diagram in solution
manager
Emma
Issue resolved
Bug is fixed,
request replied to
Emma and
Emma confirmed
the issue is fixed.

Exercise 1
Create Process Diagram

386
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Access Solution Documentation
Explanation
1. Open T - CODE SOLDOC
2. &KRRVH³%XVLQHVV3URFHVV´

387
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Create Process Diagram
Explanation
1. &OLFN³6DOH´
2. &OLFN³2UGHU WR&DVK´
3. Right Click on the empty table
4. &UHDWH³3URFHVV'LDJUDP´
5. Maintain required information
6. Specify responsible staff
7. Save

388
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Create Process Diagram (cont.)
Explanation
1. &KRRVH³2UGHUWR&DVK´'LDJUDP
2. Add all process steps

Exercise 2
Incident Handling

390
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Create Incident
Explanation
1. Open SM_CRM, choose
SOLMANREQU
2. &OLFN³&UHDWH,QFLGHQW´
3. Enter required information
4. Select System / Category
5. Upload Attachment
6. Confirm & Send

391
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Dispatch Incident
Explanation
1. Open SM_CRM, choose
SOLMANDSPTCH
2. Find incident waiting to be
dispatched
3. Click incident number
4. Dispatch incident to related
resource
5. &KDQJHVWDWXVWR³)RUZDUGHG´
6. Enter internal memo
7. Save the change

392
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Proceed Incident
Explanation
1. Open SM_CRM, choose
SOLMANPRO
2. Find incident that assigned to
current user
3. Click incident number
4. &KDQJHVWDWXVWR³,Q3URFHVV´
5. Identify issue
6. &OLFN³&UHDWH)ROORZ - XS´%XWWRQ
7. &KRRVH³5HTXHVWIRU&KDQJH´

Exercise 3
Change Processing

394
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Create Request for Change
Explanation
1. Enter required information
2. Specify Change Manager
3. Enter description of change
4. Save the change

395
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Approve Request for Change
Explanation
1. &KDQJHVWDWXVWR³,Q 9DOLGDWLRQ´
2. Specify affected landscape /
project / type of change
3. &KDQJHVWDWXVWR³7R EHDSSURYHG´
4. Approve Change
5. &KDQJHVWDWXVWR³%HLQJ
LPSOHPHQWHG´

396
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Proceed Urgent Change
Explanation
1. Click UC ID in Request for Change
2. Specify Developer / Tester / IT
Operator
3. &KDQJHVWDWXVWR³,Q
'HYHORSPHQW´
4. Perform change in development
system
5. &KDQJHVWDWXVWR³7R EH7HVWHG´
6. Perform change in test system
7. &KDQJHVWDWXVWR³6XFFHVVIXOO\
7HVWHG´
8. Approve change
9. Import change into Production
system
10. Confirm Change

397
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Confirm Request for Change
Explanation
1. Navigate to previous request
for Change
2. Check status under
³,PSOHPHQWHG´
3. &KDQJH VWDWXVWR³&RQILUPHG´
4. Check previous incident, the
status will change to
³3URSRVHG6ROXWLRQ´
5. Add Reply to the incident
6. Save the Change

398
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Confirm Incident
Explanation
1. Open SM_CRM, choose
SOLMANREQU
2. Find incident that requires further
action
3. Click incident number
4. Verify solution
5. &OLFN³&RQILUP´EXWWRQWRFRQILUP
incident

399
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Summary
You should now be able to:
9 Create Process Diagram
9 Create / Dispatch / Process an incident
9 Request a change / Process a change

Thank you.

PUBLIC
SAP Digital Business Service China
Lecture: The Business Networks
SAP Cloud Products overview

402
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

403
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
ƒ Overview
ƒ HR Cloud ± SuccessFactors
ƒ Customer Cloud ± Hybris
ƒ Procurement Cloud ± Ariba Networks
ƒ Travel Cloud ± Concur
Agenda

404
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Goals
This course will prepare you to u
‡ Understand the big picture of SAP cloud offerings related to Line
of Business and Business Networks
‡ Understand the value proposition and overall feature of SAP
SuccessFactors, Hybris Customer Engagement Cloud, Ariba
Network and Concur Travel

Overview

406
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Immediate
Empowering business users with
insights to act in the moment.
Intelligent
Beyond automation,
to predictive suggestion.
Integrated
Not only between your departments,
but connected to the world.
The Big picture about Business Solutions
Consumer experience
omni - channel
Workforce
engagement
Assets &
Internet of
Things
Supplier collaboration
business netw orks

407
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SAP S/4HANA Cloud: The Digital Core for Live Business
Workforce
Engagement
Spend
Management
Customer
Experience
IoT and
Supply Chain
MACHINE LEARNING)
APIs
SECURITY
Digital Core
S/4HANA
SAP Digital Boardroom
Business
Transactions
Intelligent
Insights
INDUSTRY
SAP HANA SAP Cloud Platform

408
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Overview
Your prospective customer wants to achieve one of the
following:
ƒ Scenario 1: Become an employer of choice and control costs associated
with both their full time and contingent workforce (Hint:
www.successfactors.com & www.fieldglass.com )
ƒ Scenario 2: Streamline and standardize procurement processes (Hint:
www.ariba.com )
ƒ Scenario 3: Control travel costs and streamline travel expense
submissions and approvals for a highly mobile workforce (Hint:
www.concur.com )
ƒ Scenario 4: Establish an online store with a world class customer
experience and a digital marketing strategy (Hint: www.hybris.com )

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Lines of Business (LoBs) & Business Netw orks
LoB/Business
Netw ork
LoB CEC LoB HR LoB Procurement
(incl. Ariba Netw ork)
Concur
(Finance &
Procurement)
SAP Fieldglass
(HR & Procurement)
Primary
Solution(s)
‡ SAP hybris ‡ SAP SuccessFactors
(SFSF)
‡ SFSF Employee
Central (EC)
‡ SAP Ariba
(Solutions) +
‡ SAP Ariba Network
Concur SAP Fieldglass
Acquired 2013 (~$1B) 2012 (~$3B) 2012 (~$4B) 2014 (~8B$) 2014 (~$1B)
Value ‡ Revenue 9
‡ Churn ;
‡ Upsell/cross - sell 9
‡ «
‡ Process Cost ;
‡ Time to Hire ;
‡ Time to Productivity ;
‡ Retention 9 /
Attrition/Churn ;
‡ Employee
Engagement 9«
Very strong business
case!
‡ Price ;
‡ 3URFHVV&RVW;
‡ &RPSOLDQFH9
‡ Cash Flow Benefits
9
Similar to Ariba, but
for T&E
‡ Efficiency 9
‡ Cost ;
‡ Worker quality 9
‡ Compliance 9
Customers &
Other Resources
‡ Fast Facts
‡ www.hybris.com
‡ Corning (S4HC
customer)
‡ Fast Facts
‡ www.successfactors.c
om
‡ www.sap.com/hr
‡ Fast Facts
‡ www.ariba.com
www.concur.com www.fieldglass.com

HR Cloud ± SuccessFactors

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You know that feeling
when you walk through a
FRPSDQ\¶VIURQWGRRU
<RXFDQIHHOWKHHQHUJ\«
6RPHWLPHVLW¶VIODW
2WKHUWLPHVLW¶VHOHFWULF
And what drives that
energy?

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Your People.
They are the heartbeat of
your organization.
When they are engaged ±
feeling supported, trained,
rewarded and motivated ±
they will do what it takes
to win.

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Engaged People =
Extraordinary Results
71% of respondents rank
employee engagement as
imperative to achieving
business success.
Harvard Business Review
7KLVKHDUWEHDWSURYHV«
7 1
%

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Workplace
Complexity
Evolving
Workforce
Battle
for Talent
%XWWKHG\QDPLFVRIHQJDJLQJSHRSOHDUHFKDQJLQJ«
© 2016 SAP SuccessFactors All rights reserved. 414

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Across the total workforce
Mastering these challenges requires a digital approach to HR
HCM technology must encompass a new set of digital capabilities
Encourage continuous usage
and engagement , and foster
continuous innovation
Use data to suggest and
recommend
Expand solutions and
build ow n apps to meet
current and future needs.
IntelligentContinuous Extensible

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SAP SuccessFactors HCM Suite
Unmatched breadth and depth of solutions
Competencies | Skills | Best Practices
Core HR
Recruiting Learning
Performance
& Goals
Succession &
Development
Employee Recordkeeping | Organizational Management | Global Benefits
Shared Services | Payroll | Time & Attendance
Talent Management
Technology : Secure | Integrate | Extend
User Experience: Social | Mobile | Intelligent Services
Compensation
Onboarding
Reporting & Embedded Insight Workforce Analytics
Workforce Planning

Demo
SAP SuccessFactors

Customer Cloud ± Hybris

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DIGITAL TECHNOLOGIES HAVE QUICKLY BECOME A DRIVING FORCE OF JOB CREATION,
ENTREPRENEURSHIP, AND INNOVATION IN THE 21ST CENTURY. JUST A DECADE AGO,
LESS THAN A FIFTH OF THE GLOBAL POPULATION HAD INTERNET ACCESS.
TODAY, 3.2 BILLION PEOPLE ARE ONLINE. BY 2020, THAT NUMBER WILL GROW TO FIVE
%,//,213(23/(7+$76$0(<($57+((0(5*,1*³,17(51(72)7+,1*6´6(&725
WILL LIKELY COMPRISE A $1.7 TRILLION GLOBAL MARKET. BY 2025, PRODUCTS AND
SERVICES THAT RELY ON CROSS - BORDER DATA FLOWS WILL ADD $1 TRILLION
ANNUALLY TO THE GLOBAL ECONOMY.
Penny Pritzker
Secretary, US Department of Commerce
June 22, 2016

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&+$1*(,6+$33(1,1*)$67(57+$1(9(5«
TIME TO REACH
50 MILLION
USERS
75 YEARS
38 YEARS
13 YEARS
4 YEARS
3.5 YEARS
3 YEARS
2.5 YEARS
50 DAYS
35 DAYS

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CUSTOMERS ARE HARDER TO ENGAGE

of online ads are ignored.
Source: Google

of the buying process is
completed before a first
interaction with sales.
Source: Customer Executive Board

of consumers abandoned
a purchase due to a poor
service experience.
Source: American Express Global Barometer

CHANGE
ADDRESS
DISCOVER
NEED
RECEIVE
OFFER
POST
REVIEW
MAKE
PAYMENT
JOIN
GROUPS
SHORTLIST
TRACK
ORDER
BUY
RECEIVE
PACKAGE
SET UP
PHONE
MISSING
ITEM
NETWORK
ISSUE
FIX
ISSUE
RESTART
SERVICE
BILLING
ISSUE
LOYALTY
BONUS
RECEIVED
OFFER
W EB
TV
DIGITAL
ADS
PRINT
SOCIAL
SEARCH
KW /ADS
REVIEW S
RETAIL
STORE
CONTACT
CENTER
EMAIL
SOCIAL
CONTACT
CENTER
SUPPORT
PORTAL
CONTACT
CENTER
SOCIAL
BRANDED
COMMUNITY
CONTACT
CENTER
CONTACT
CENTER
RETAIL
STORE
AWARENESS
INTEREST
CONSIDERATION
ACTION
USE
ACTION
ADVOCACY
ADVOCACY
CONSIDERATION
USE
SUPPORT
PORTAL
WEB
SHOP
RETAIL
STORE
REFER
FRIENDS
EMAIL
SOCIAL
W ORD OF
MOUTH
W EB
SITE
W ORD OF
MOUTH
W EB SHOP
RESEARCH
W EB
W EB SHOP
DISCOVERY
EACH CUSTOMER
CHOOSES THEIR
OWN ADVENTURE

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73%
of businesses recognize
the challenge posed by
competitors who make
better use of customer
data, analytics and
engagement.
,7¶67,0(72$&7

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BUT THE
CHOICES ARE
OVERWHELMING,
AND ASSEMBLING
DISPARATE
SOLUTIONS CAN
MAKE THINGS
WORSE.
SOURCE: chiefmartech.com

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426
CRM. WEB CMS. MOBILE. MARKETING. OMS.
STORES. CONTACT CENTERS. ETC.
THIS
COMPLEXITY
MAKES AGILITY
IMPOSSIBLE.

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WHAT MAKES SAP HYBRIS DIFFERENT?
WE ATTACK OF THE PROBLEM

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OUR APPROACH
W EB M OBILE IOT SOCIAL
EM AIL PRINT AGENT
TOOLS
EXPERIENCE MANAGEMENT
PLATFORM, INFRASTRUCTURE, INTEGRATION
DATA & PROCESS MANAGEMENT
COMMERCE SERVICEBILLING SALESMARKETING
IN STORE/
BRANCH
CONTACT
CENTER
M ARKET -
PLACE
SM S/
NOTIFICATION
SEARCH
ADS / SEO
DIGITAL
ADS
DIGITAL
GOODS

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SAP Hybris Commerce Cloud drives your digital transformation and enables you
to become an omni - channel business , deliver contextual customer experiences
and respond to the market faster .
SAP HYBRIS COMMERCE CLOUD
Commerce for B2C & B2B
Customer Experience
Customer Support
Merchandising Mobile Tools
Order Management
Product Content Management
Search
KEY CAPABILITIES

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SAP Hybris Billing is an end - to - end solution for subscriptions and usage - based
service monetization . With coverage of the entire offer - to - cash process , it allows
you to rapidly launch customer - centric subscription offers ; exploit fast - moving
market opportunities ; build both simple and sophisticated pricing models ; and
seamlessly incorporate partner revenue sharing models .
SAP HYBRIS BILLING
Billing & Revenue Management
Subscription Order Management & Pricing Agility
Usage Mediation & Service Control
Partner Revenue Share
Business Model Design & Pricing Simulation
KEY CAPABILITIES

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SAP Hybris Marketing Cloud enables organizations to market in the moment
by allowing marketers to understand the real - time intent of each customer and
dynamically deliver contextually relevant experiences across channels .
SAP HYBRIS MARKETING CLOUD
Consumer & Customer Profiling
Segmentation & Campaign Execution
Marketing Resource Management
Commerce Marketing Loyalty Management
Marketing Lead Management
Marketing Analytics
Customer Journey Manager
KEY CAPABILITIES

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SAP Hybris Sales Cloud is a modern - day , cloud sales solution that is built for
sales professionals on the go . Leveraging user experience technology that is
easily tailored to the way companies want to engage with their customers and
run their business .
SAP HYBRIS SALES CLOUD
Analytics
Mobility
Opportunity Management
Retail Execution Territory Management
Sales Performance Management
Sales Force Automation
Collaboration
KEY CAPABILITIES

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SAP Hybris Service Cloud solutions enable the end - to - end service process ;
supporting seamless transitions between communication channels to
resolve customer issues and execute service orders through self -
service options , engagement center agents or an on - site technician .
SAP HYBRIS SERVICE CLOUD
Call Center Management
Field Service Management
Mobility
Workflows and Approvals Analytics
Knowledge Base
Ticket Management
Omni - Channel
KEY CAPABILITIES

Demo
SAP Hybris

Procurement Cloud ± Ariba Network

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Top Priorities of Procurement
28%
27%
17%
24%
17%
18%
17%
14%
18%
44%
42%
51%
43%
43%
39%
40%
39%
32%
Role of procurement as trusted advisor
Reduce/avoid purchase cost
Improve procurement's business agility
Expand scope/influence
Deepen influence on complex indirect spend
Enable innivation/tap supplier innovation
Increase internal stakeholder satisfaction
Reduce supply risk
Improve supplier delivery performance
Critical Issues Major Issues
Key Issues Study, The Hackett Group, 2015
(OHYDWLQJ³5ROHRISURFXUHPHQW DVD
WUXVWHG DGYLVRU´DSSHDUVDVWRSSULRULW\
It involves participate in budgeting &
planning cycles by providing
± Cost insights into less expensive
alternatives
± Ensuring optimal RoI on
investments
Reducing purchase costs still continue
to dominate top priorities
Issues Responded by Respondents in Procurement Role

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Performance of World - Class Procurement Organizations
World - class procurement organizations continue their record of outperforming
their peer group by a wide margin
World - class procurement organizations deliver higher - quality services at:
27%
Lesser costs Lesser FTEs
19%
Procurement Executive Insight, The Hackett Group, 2014

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Some Key Performance Indicators..
World - class procurement organizations as compared to their peers
0.59%
0.73%
World-Class Peer Group
19%
9.01
4.06
World-Class Peer Group
122%
World - class procurement organizations
have 19 % lesser procurement cost as
% of their spend than their peer group
World - class procurement organizations
have 9 X payback on investment
This is 122 % higher than their peer
group
Procurement Executive Insight, The Hackett Group, 2014
12,713
3,738
World-Class Peer Group
240%
In PO processing efficiency world -
class procurement organizations beat
their peer group by a large margin of
240 %

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SAP Ariba cloud applications and Business Network
Uniquely positioned to address diverse spend categories, suppliers and processes
DIRECT AND SUPPLY CHAIN
INDIRECT AND MRO
User Experience + SAP HANA Cloud Platform + INTEGRATION TO SAP AND NON SAP S/M
S o u rce & C o n t ract Request & Buy Invoice & Pay
ContractSourcePlan OrderApproveRequest PayManageReceive
Supplier Management

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Delivers measurable benefits and value to companies of all sizes,
industries, regions
Source: SAP Ariba customer surveys and interviews
BUYER VALUE
SELLER VALUE
Unit Price
Reduction
Procuremen
t Process
AP Process
Contract
Compliance
WCM &
Discount
3 - 9%
Sourcing
Savings
4 - 7%
Procure - to - Pay
Savings
Faster
Payment
AR Process
Processing
Orders
Sales &
Marketing
Increased
Revenue
15 - 75%
Time
Savings
15 - 75%
Process
Savings
5 - 32%
Revenue
Increase

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Drive business transformation through new innovations
44
1
Total User Experience
Work Anywhere
Learn in Context
Modern UX Principles

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Drive business transformation through new Innovations
44
2
AribaPay
Simple. Certain. Secure
Buyer
Paym ent
instructions
Rich
rem ittance
Track and trace
paym ent status
Bank account
management
Invoice status
Purchase
orders,
invoices,
contracts, and
receipts
Supplier
Buyer
Bank
Supplier
Ban
k
Debit
Credit
Integrate Payment with Data
32¶V,QYRLFHV
Contracts,
Receipts
AribaPay

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Drive business transformation through new Innovations
44
3
SHIP
ECOSYSTEM
OF SUPPLY
APPROVE PAY
SEARCH
BUYING
ORGANIZATIONS
Ariba Procurem ent
ANALYZE
FILTER
Seller Direct
M arketplaces
ƒ Reduce time and effort to find and buy non - sourced goods
ƒ Bring non - sourced spend under control
ƒ ([SDQGSURFXUHPHQW¶VDELOLW\WREHWWHUVHUYHWKHLUFXVWRPHUV
Ariba Spot Buy ± Find and Buy Non - Sourced Goods
The perfect balance of convenience and control
‡ Filtered suppliers and content
‡ Thousands of categories
‡ Regionally available supply
‡ Simple user experience
‡ Configuration and workflow
‡ Secure payment
‡ Visibility into detailed data

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Drive business transformation through new Innovations
44
4
BUYING ORGANIZATION TRADING
PARTNER
Goods
receipt notice
Purchase order or
change order
Ship notice
Order confirmation
Invoice
Collaborative Supply Chain ± Extended Order Management

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Netw ork Collaboration ± Driving Buyer and Seller Value
Customer success ± Buy side
$800 million in savings
within a span of 4 years
> 30% reduction in
BPO costs
75% reduction in invoice
approval and processing
times
18% savings for categories
managed through SAP Ariba
3,000+ suppliers onboarded
and
7,500 + contracts managed
Maersk Deutsche Bank
AmBank Posadas
AIR FRANCE KLM

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Netw ork Collaboration ± Driving Buyer and Seller Value
Customer success ± Sell side
MEDIAFLY STEELCASE MARK MASTER Charles Seafood
Grew orders with
existing customers
>65%. 20%+
Y - o - Y revenue gain
for 6 years.
Gained 80% of new
clients through Ariba
Network
Cut quote - to -
settle cycle by
Purchase order
process reduced
from several w eeks
to hours
30% reduction in
days sales
outstanding
80% reduction in
late payments
84%
Taps early
payment
discounts to
improve
cash flow, fund
investments.
Faster
Payment
Higher Customer
Satisfaction
Increase
Sales
Low er Customer
Service Costs

Demo
SAP Ariba Networks

Travel Cloud ± Concur

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449
One day in Concur
> 1 Mio. end user
> 170.000 trips booked by clients
> 700.000 expense reports transferred
We are archiving 180 Mio. database entries
We are initiating reimbursement of 0LR¼

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- 450 -
Core products
Request &
book journey
Expense
journey
Invoice &
report
Approve
booking
Approve
expenses
Conduct
journey
1
2 3 4 5 6
Concur Travel
Concur Expense
Concur Request
Concur Mobile Apps
Concur platform
Concur Intelligence
Tripit Concur Mobile Expenseit
We offer an end - to - end solution to manage T&E
End - to - end travel and expense coverage
Concur Messaging
Services
T his how 40.000 custom ers worldwide are driving value and m ak ing better business decisions around their discretionary spend b y p artnering with concur.

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- 451 -
Intangible benefits further speak for a harmonization
Concur Travel & Expense benefits by stakeholder
Concur Travel & Expense:
9 State - of the art user
interface
9 Very solid data base
9 Full end - to - end coverage
User:
‡ Always know s w hat he is
allow ed to book
‡ Great mobile apps
‡ Clear guidance for approvals
‡ Effortless booking and expense
Manager:
‡ Gets proactively informed
and guided in approvals
‡ Can centrally manage all requests
± mobile and browser based
‡ Can control spend proactively
HR / travel manager / IT:
‡ Easy to admin system
‡ High flexibility in policy
adjustments
‡ Compliance monitoring and
powerful reporting
Finance / procurement / risk:
‡ Tight cost control
‡ Improved negotiation pow er
‡ Pow erful audit tools
‡ State - of - the art Concur
Messaging

Demo
SAP Concur

Recap of the Semester 1

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SAP Implementation
and Value Assurance
Services
Semester Recap
SAP Leonardo
Innovation Services
SAP HANA SAP Cloud Platform
System of
Record
SAP S/4HANA
SAP Hybris
SAP
SuccessFactors
Concur
SAP Fieldglas
SAP Ariba
System of
Innovation
SAP Leonardo
IoT
Machine Learning
Big data
Modern Analytics
Blockchain
Data Intelligence
Semester 1
Semester 2

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Course Summary
You should now be able to:
9 Understand the big picture of SAP cloud offerings related to Line
of Business and Business Networks
9 Understand the value proposition and overall feature of SAP
SuccessFactors, Hybris Customer Engagement Cloud, Ariba
Network and Concur Travel

Thank you.

PUBLIC
SAP Digital Business Service China
Hands on
SAP SuccessFactors

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
ƒ Scenario1
ƒ Exercises
± Job Requisition Process ± SA P & SUCCESS F AC T ORS
± SuccessFactors Hybrid Demo (Scenario2)
± Investigate - SuccessFactors Workforce Anal y tics
Agenda

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Course Goals
This course will prepare you to u
‡ Create vacant position in SAP
‡ Create a Leave request
‡ Create a Workforce Anal y tics page

Scenario1

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Scenario1
Emma using Success
Factors to create the job
requisition quickly
together with updating
Requisition ID in SAP,
and then send it to her
Manager.
Success Factors
HCM
HR Emma
Manager using HCM
with just a few clicks,
she approves and
sends job requisition
to Recruiter for further
processing.
*Screenshots shown are for dem onstration purposes only and are not final product com mitments
manager wants to
hire a new employee
Emma is an HR. Her
manager wants to hire a
new employee, and asks
her to create a Job
Requisition .

Exercise 1
Job Requisition Process ± SA P & SUCCESS F AC T ORS

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Job Requisition Process ± SA P & SUCCESS F AC T ORS (1/6)
Explanation
1. Enter ec3 in the Search text field.
2. Double Click
3. Enter User and password.
4. Note: HR Administrator creates
vacant position in SAP: The HR
Professional creates a vacant
position in the Organizational
Management module of SAP. This
ensures that a job requisition is
triggered.
5. Enter ppome in the Transaction
text field.
6. Click .

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Job Requisition Process ± SA P & SUCCESS F AC T ORS (2/6)
Explanation
1. Click
2. Click
3. Right Click on Sales Analyst &
Select Copy
4. &OLFN³2.´
5. Note: 6WDIILQJVWDWXV¶ILHOGKDVWKH
µ9DFDQF\RSHQ¶VHOHFWLRQ
6. Click Save

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Create Job Requisition Process ± SA P & SUCCESS F AC T ORS (3/6)
Explanation
1. Click
2. Note: µ6)6)-RE5HTXLVLWLRQ¶WDE
for the position has the below
fields updated:
1. µ5HTXLVLWLRQ6WDWXV¶RIµ7REH
&UHDWHG¶
2. µ5HTXLVLWLRQ7HPSODWH,'¶
has SuccessFactors job
requisition template ID 1492
These fields must be updated to
trigger the job requisition in
SuccessFactors
3. Click

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Job Requisition Process ± SA P & SUCCESS F AC T ORS (4/6)
Explanation
1. Enter HRSFI_RCT_TRG_JOBREQ
in the Transaction text field.
2. Click .
3. Click
4. Enter ppome in the Transaction
text field. Note: µ5HTXLVLWLRQ
6WDWXV¶XSGDWHGWRµ&UHDWHG¶DQG
WKHµ5HTXLVLWLRQ,'¶KDVEHHQ
updated with the job requisition
number from SuccessFactors
5. Click Note: The
µ6KRZ)LHOGV¶EXWWRQRQWKLV
infotype will display all the
information transferred across to
SuccessFactors

468
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Job Requisition Process ± SA P & SUCCESS F AC T ORS (5/6)
Explanation
1. /RJRQE\XVLQJWKHPDQDJHU ¶V
account. Note: Manager checks
the job requisition has been
created and forwards to Recruiter
2. Click
3. Click
4. Click
5. Click

469
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Job Requisition Process ± SA P & SUCCESS F AC T ORS (6/6)
Explanation
1. Click Department
2. Select .
3. Click Location
4. Select
5. Click
6. Uncheck
7. Uncheck
8. &OLFN³1H[W´
Note: The job requisition has now
been approved and sent to the
recruiter for further processing.

Exercise 2
SuccessFactors Hybrid Demo

471
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Scenario2
He then reviews his
goals in the goal
management systems
and sets time aside to
finish some goal related
tasks.
leave
application
system
the goal
management
systems
Performance
Review
systems
Marcus
Carla Grant, a
General Manager,
goes to Performance
Review systems and
ORRNVDW0DUFXV¶
goals to see how he
is going on his goals.
*Screenshots shown are for dem onstration purposes only and are not final product com mitments
Marcus applies for family
leave using the leave
application system. He
then adds his new born
baby as a dependent in
the benefits system.
Carla approves
the family leave
Carla approves the
family leave along
with a note asking
Marcus to attend to
one goal before he
leaves for vacation.

472
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SuccessFactors Hybrid Demo (1/9)
Explanation
1. This demo highlights the seamless
navigation across SAP Employee
Self Service and Manager Self
Service applications and
SuccessFactors Business
Execution Suite of applications,
particularly goal management.
2. &OLFN³/RJRQ´E\XVLQJ0DUFXV¶
account
3. &OLFN³/HDYH5HTXHVW´0DUFXV
Hoff applies for Family Leave)
4. Click to choose Start date
5. Choose 4
th
Aug as Start date
6. Choose 9
th
Aug as End date

473
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SuccessFactors Hybrid Demo (2/9)
Explanation
1. Enter This is a family leave to be
with the new born child in the box.
2. &OLFN³6HQG´WRVHQGWKHOHDYH
request.
3. 7KHQ&OLFN³2.´
4. The leave request has been sent
to the manager, Click to
close the page.

474
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SuccessFactors Hybrid Demo (3/9)
Explanation
1. &OLFN³(PSOR\HH6HUYLFH´
2. &OLFN³%HQHILWVDQG3D\PHQW´
3. 7KHQ&OLFN³'HSHQGHQWVDQG
%HQHILFLDULHV´

475
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SuccessFactors Hybrid Demo (4/9)
Explanation
1. Notes: Click on the Add button to
add child as a beneficiary You can
add all information or Cancel out of
the screen
2. Click to go back
3. &OLFN³(PSOR\HH6HUYLFH´
4. &OLFN³&DUHHUDQG'HYHORSPHQW´
5. &OLFN³*RDOV´
6. &OLFN³6WDWXV5HSRUW´

476
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SuccessFactors Hybrid Demo (5/9)
Explanation
1. You can see the Status Report for
Marcus, then Click
2. &OLFN³6LJQRII´
3. &OLFN³/RJRQ´E\XVLQJ&DUWD¶V
0DUFXV¶PDQDJHUDFFRXQW
4. &OLFN³0DQDJHU6HUYLFHV´

477
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SuccessFactors Hybrid Demo (6/9)
Explanation
1. &OLFN³7R'RV´WRFKHFNPDQDJHU ¶V
to do work
2. &OLFN³0DQDJHU6HUYLFHV´
3. &OLFN³3HUIRUPDQFH5HYLHZIRU
0DUFXV+RII´
4. &OLFN³*RDOV´

478
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SuccessFactors Hybrid Demo (7/9)
Explanation
1. 5HYLHZ0DUFXV¶*RDODQGWKHQ
Click
2. Click ³0DQDJHU6HUYLFHV´
3. &OLFN³5HSRUWV´DQGWKHQ&OLFN
³$QDO\WLFV´

479
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SuccessFactors Hybrid Demo (8/9)
Explanation
1. Note: There should show the
analytics report, but this demo
GRHVQ¶WKDYHWKHUHSRUW
2. Click to close the page.
3. Click ³0DQDJHU6HUYLFHV´
4. &OLFN³7DOHQW0DQDJHPHQW´DQG
WKHQ&OLFN³6XFFHVVLRQ3ODQQLQJ´

480
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
SuccessFactors Hybrid Demo (9/9)
Explanation
1. Succession Org Chart will show,
manger can use this to arrange
successor for employees
2. Click to close the page

Exercise 3
Investigate - SuccessFactors Workforce Anal y tics

482
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Investigate - SuccessFactors Workforce Anal y tics (1/9)
Explanation
1. 2.1.1 BestRun finds that they need
to analyze their retention based on
a gender analysis as a part of
diversity and inclusion
2. &OLFN³´
3. &OLFN³,QYHVWLJDWH´
4. &OLFN³1HZ´

483
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Investigate - SuccessFactors Workforce Anal y tics (2/9)
Explanation
1. 2.1.2 Investigate External Hire
Rate by Gender
2. &OLFN³´
3. Search external and Click
³ External Hire Rate ´
4. 6HDUFKJHQGHUDQG&OLFN³ Gender ´

484
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Investigate - SuccessFactors Workforce Anal y tics (3/9)
Explanation
1. The chart area shows the chart of
³([WHUQDO +LUH5DWH´ZLWKWKH
PHWULF³*HQGHU´
2. &OLFN³7DE´
3. Rename the Canvas and then
&OLFN³6DYH´

485
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Investigate - SuccessFactors Workforce Anal y tics (4/9)
Explanation
1. 2.1.3 Further Investigation ±
Retention Rate by Gender
2. Click ³´
3. Click to Add a new tab
4. Search retention and Click
³5HWHQWLRQ5DWH´
5. 6HDUFKJHQGHUDQG&OLFN³*HQGHU´

486
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Investigate - SuccessFactors Workforce Anal y tics (5/9)
Explanation
1. The chart area shows the chart of
³5HWHQWLRQ5DWH´ ZLWKWKHPHWULF
³*HQGHU´
2. &OLFN³5HQDPH´ WRUHQDPH WKH
FDQYDVDQGWKHQ&OLFN³6DYH´

487
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Investigate - SuccessFactors Workforce Anal y tics (6/9)
Explanation
1. 2.1.4 Further Investigation ±
Retention Rate by Gender and
Supervisor
2. Click ³´
3. Click and then Click
³'XSOLFDWH´WRGXSOLFDWHWKHWDE
4. &OLFNWRUHPRYHPHWULF³DOO
WLPHSHULRGV´

488
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Investigate - SuccessFactors Workforce Anal y tics (7/9)
Explanation
1. 6HDUFK³VXS´ DQGWKHQ&OLFN
³6XSHUYLVRU´
2. &OLFN³'DQLHO&RUWH]´
3. The chart area shows the chart of
³5HWHQWLRQ5DWH´ ZLWKWKHPHWULF
³*HQGHU´ DQG³'DQLHO&RUWH]´
4. &OLFN³$QDO\]H´

489
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Investigate - SuccessFactors Workforce Anal y tics (8/9)
Explanation
1. &ORVH³)RUHFDVW´
2. &OLFN³&ROXPQ´DVWKHDQDO\]H
chart
3. &OLFN³$GGWR&ROOHFWLRQ´

490
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Investigate - SuccessFactors Workforce Anal y tics (9/9)
Explanation
1. &OLFN³$GG´
2. Click to see
collections
3. Click to View and share the
"Collection"

491
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Summary
You should now be able to:
9 Create vacant position in SAP
9 Create a Leave request
9 Create a Workforce Analytics page

Thank you.

PUBLIC
SAP Digital Business Service China
Hands on
Customer Engagement Cloud

494
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

495
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
ƒ Scenario
ƒ Exercises
± Applying for a Credit Card in SAP Hybris Commerce
± Providing Service for the Customer in C4C(Cloud for
Customer)
Agenda

496
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Goals
This course will prepare you to u
‡ Be able to apply a credit card in SAP Hybris Commerce
‡ Providing Service for the Customer in C4C (Mortgage)

Scenario

498
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Scenario
Emma gets her credit
card, but she still needs
a large amount of money
to pay the house rent
near the MBA college.
Hybris Banking
Cloud for Customer
Emma
Chris help Emma
apply mortgage with
Cloud for Customer,
only a few steps and
then Emma get her
mortgage quickly.
*Screenshots shown are for dem onstration purposes only and are not final product com mitments
I successfully applied
an MBA program, but
I need some money to
cover education fee.
Emma could apply for a
Credit Card in SAP
Hybris Commerce, just
with a few clicks, it will
be done.
Need more money

Exercise 1
Applying for a Credit Card in SAP Hybris Commerce

500
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Applying for a Credit Card in SAP Hybris Commerce (1/5)
Explanation
1. Click the vertical scroll bar to
display the desired screen area
2. Click the Hybris Bank banner
3. Click the vertical scroll bar to
display the desired screen area

501
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Applying for a Credit Card in SAP Hybris Commerce (2/5)
Explanation
1. &OLFN³6WDUW$SSOLFDWLRQ´
2. &OLFN³%X\´
3. Then it goes to the personal details
page

502
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Applying for a Credit Card in SAP Hybris Commerce (3/5)
Explanation
1. Fill out all the information needed
2. Click t h e a rr o w t o o p e n th e d r o p -
d o w n list f o r th e Coun t ry f i e ld
3. S e l e ct Uni t e d S t a t es

503
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Applying for a Credit Card in SAP Hybris Commerce (4/5)
Explanation
1. &OLFN³&RQWLQXH´
2. You can see Quote Review, Click
³&RQWLQXH´WRPRYHIRUZDUG
3. &OLFN³&21),50´WRFRQILUPDOOWKH
information

504
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Applying for a Credit Card in SAP Hybris Commerce (5/5)
Explanation
1. &OLFN³&RPSOHWH$SSOLFDWLRQ´
2. T h e a pplic a ti o n h a s b ee n s e nt

Exercise 2
Providing Service for the Customer in C4C(Cloud for
Customer)

506
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Providing Service for the Customer in C4C (1/9)
Explanation
1. &OLFN³/RJRQ´ to SAP Cloud for
Customer by using chri s . l e e ¶V
account
2. &OLFN³ SERVICE ´
3. &OLFN³7,&.(76´
4. Click the arrow next to Tickets:
Tickets From Last 7 Days (10) to
open a drop - down list.

507
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Providing Service for the Customer in C4C (2/9)
Explanation
1. &OLFN³ $OO7LFNHWV´
2. &OLFN³ 5157 ´
3. Click
4. &OLFN³$&7,9,7,(6´

508
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Providing Service for the Customer in C4C (3/9)
Explanation
1. &OLFN³ 1HZ´
2. (QWHU³7RP B en s on ´ in th e
A ccount f i e ld
3. E nt e r J ohn in th e O w n er f i e ld.
4. S e l e ct J ohn Da v i s

509
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Providing Service for the Customer in C4C (4/9)
Explanation
1. &OLFN³6DYH ´
2. Click to log out
3. &OLFN³<HV´
4. &OLFN³5HVWDUW$SSOLFDWLRQ´

510
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Providing Service for the Customer in C4C (5/9)
Explanation
1. &OLFN³/RJRQ´WR6$3&ORXGIRU
Customer by using john. d a v i s ¶
account
2. &OLFN³$&7,97,(6´
3. Click
4. Click ³0RUH´

511
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Providing Service for the Customer in C4C (6/9)
Explanation
1. &OLFN³7RP%HQVRQ´
2. &OLFN³ . . . ´ i n th e t a b b a r i n t h e u pp e r
p a r t o f th e sc r ee n.
3. &OLFN³ yMarketing $FFRXQW,QIR´

512
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Providing Service for the Customer in C4C (7/9)
Explanation
1. You should be able to see the
customer fact sheet in SAP Hybris
Marketing without having to log on.
2. Click button to close the
window
3. Click button again to close the
window
4. &OLFN³6(59,&(´

513
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Providing Service for the Customer in C4C (8/9)
Explanation
1. &OLFN³7,&.(76´
2. &OLFN³´
3. &OLFN³:HE6HUYLFHV´

514
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Providing Service for the Customer in C4C (9/9)
Explanation
1. Click Launch Mortgage Application
online
2. Click a n y w h e r e o n th e sc r ee n t o
e n d t h e sc e n a r i o

515
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Summary
You should now be able to:
9 Be able to apply a credit card in SAP Hybris Commerce
9 Providing Service for the Customer in C4C (Mortgage)

Thank you.

PUBLIC
SAP Digital Business Service China
Hands on
Ariba

518
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

519
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
ƒ Scenario
ƒ Exercises
± Create request for quotation (RFQ) in SAP ECC
± Process & Publish event in Ariba Sourcing
± Submit Supplier ¶s Bid
Agenda

520
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Goals
This course will prepare you to learn u
‡ Easy integration with SAP ECC and Ariba
‡ Simple Web interface for Suppliers via Ariba Supplier Network
‡ Create a Strategic Sourcing Request in ECC
‡ Process & Publish event in Ariba Sourcing
‡ Submit Supplier bids

Scenario

522
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Scenario
Once the quote is sent
out to bid, suppliers
response and the bids
are analyzed.
Ariba
$QDO\]H«
ECC
The buyer can then use
the SAP Ariba solution to
draft the contract using
SAP Ariba Contract
Management or simply
make an award based on
the quotes received.
*Screenshots shown are for dem onstration purposes only and are not final product com mitments
This scenario will show an
integrated Source - to - Pay
process flow between
ECC and Ariba.
It begins by creating a
quote in ECC but using
standard integration that
quote is delivered to the
SAP Ariba Sourcing
solution so it be
collaborated on with the
suppliers over the Ariba
Network.
The SAP Ariba Solution

Exercise 1
Create request for quotation (RFQ) in SAP ECC
In this scenario, we will create an RFQ in ECC
and send to Ariba to be sourced. We will then
have the awarded bid sent back to ECC as a
Contract or a PO.

524
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Create request for quotation (RFQ) in SAP ECC (1/5)
Explanation
1. In our first step, we will create an
RFQ in ECC and then have it sent
to Ariba.
2. Access to ECC, and Log in with
User name and password .
3. Type in T - code ME41.
4. Access to the page: Create RFQ
Initial Screen.

525
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Create request for quotation (RFQ) in SAP ECC (2/5)
Explanation
1. 7\SHLQ5)47\SH³665´
2. Fill out Quotation Deadline, Use a
date that is few days out, but
before the Delivery Date.
3. )LOORXW3XUFKDVLQJ*URXS³´
4. The Regional Plant and Storage
Location field is filled out.
5. Fill out the Delivery Date. The Date
needs to be after the Quotation
Deadline Date.
6. Access to the page: Create RFQ
Header Data.

526
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Create request for quotation (RFQ) in SAP ECC (3/5)
Explanation
1. Type in Coll.No ³)UHH7;7´
2. Access to the page: Create RFQ
Item Overview.

527
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Create request for quotation (RFQ) in SAP ECC (4/5)
Explanation
1. Material: PROC - DC - PC - 0063
needs to be filled out and Hit Enter.
2. 7\SHLQ5)44XDQWLW\³´
3. Click Vendor Address button or
Y \ you can also press F7 to access
to the page : Create RFQ Vendor
Address

528
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Create request for quotation (RFQ) in SAP ECC (5/5)
Explanation
1. Type in the information needed in
the page, including Vendor, Name,
Search Terms, Street Address and
so on. All the information are
maintained as vendor address.
2. Click Save, RFQ is Created.
3. The RFQ created in SAP ECC has
been pushed into Ariba Sourcing
in the form of a Sourcing Request.

Exercise 2
Process & Publish event in Ariba Sourcing

530
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Process & Publish event in Ariba Sourcing (1/11)
Explanation
1. In this step of the demo, we are
going to login to Ariba Sourcing as
the Strategic Purchaser to review
and publish the Sourcing Request
so the suppliers can respond later.
2. Log in with User name and
password
3. 6000002448 is entered in
Sourcing Request. Then c lick

531
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Process & Publish event in Ariba Sourcing (2/11)
Explanation
4. Open the Search Result.
5. In a productive environment, the
Buyer would need to complete the
Tasks listed, but for this scenario
we will mark them complete and
move on.

532
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Process & Publish event in Ariba Sourcing (3/11)
Explanation
4. Clic k , Click
then Clic k

533
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Process & Publish event in Ariba Sourcing (4/11)
Explanation
9. )RUWDVN³$SSURYDOIRU6RXUFLQJ
5HTXHVW´YLHZ task details.
10. We will select a Fixed Date to
inform the Approver of the urgency.
11. Click
12. Select a date a few days in the
future, but before the Delivery
Date you asked for.

534
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Process & Publish event in Ariba Sourcing (5/11)
Explanation
11. Message field is filled out, and
then click Submit.
12. View Task Details again, check
Approval Flow. Then Click

535
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Process & Publish event in Ariba Sourcing (6/11)
Explanation
11. Click Documents, then open
Sourcing Project.
12. Choose Quick Project

536
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Process & Publish event in Ariba Sourcing (7/11)
Explanation
11. &KRRVH(YHQW7\SHWR³5)3´
12. Scroll Mouse wheel down to bring
the screen to desired location, then
Click Request for Proposal
13. Click

537
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Process & Publish event in Ariba Sourcing (8/11)
Explanation
11. Click , Choose a future date,
then Click
12. If you wanted to add other
participants to this event, it could
be done here (Picture 2), For this
scenario, we will skip this option.
13. Click

538
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Process & Publish event in Ariba Sourcing (9/11)
Explanation
11. Click , Enter in
the name of the first Supplier.
12. Digistorage is entered to search.
13. Click the check box , then Click OK

539
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Process & Publish event in Ariba Sourcing (10/11)
Explanation
11. Click .
12. Edit the Pump Centrifugal 1/3hp
13. Choose Commodity
14. Then Click

540
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Process & Publish event in Ariba Sourcing (11/11)
Explanation
11. Click .
12. Click , Then the Event
will be published

Exercise 3
Submit Supplier ¶ s Bid

542
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Submit Supplier ¶ s Bid (1/ 5 )
Explanation
1. In this section, we will log in as the
Supplier in the Ariba Network's
Supplier accounts. The Supplier
will review the Bid invitation and
respond back to the Buyer.
2. Log in with User name and
password.
3. Click and Choose
³3URSRVDOV´

543
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Submit Supplier ¶ s Bid (2/ 5 )
Explanation
1. If you are looking at the Proposals
from the corresponding realm,
select the realm you originated
from. Upon see a new Bid
Invitation, the Supplier will now
open the Sprucing Project and
reply back to the Buyer with their
offer.
2. Choose to Expand the
Status: Open section (not shown)
to find your Bid Invitation.

544
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Submit Supplier ¶ s Bid (3/ 5 )
Explanation
1. Click
2. Click ³ I accept the terms of this
agreement. ´ .
3. Click

545
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Submit Supplier ¶ s Bid (4/ 5 )
Explanation
1. Click to submit the
agreement.
2. After agreeing to the terms, the
Supplier will now select the item(s)
which they want to bid on.
3. Click , then Submit Selected
Lots.
4. Fill out the contents, then click
and

546
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Submit Supplier ¶ s Bid (5/ 5 )
Explanation
1. Click
2. Then choose to log out.

547
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Summary
You should now be able to:
9 Be aware of a c o m p let e l y integrated Source - to - Pa y process
flow between E CC and Ariba
9 Create a Strategic Sourcing Request in ECC
9 Process & Publish event in Ariba Sourcing
9 Submit Supplier bids

Thank you.

PUBLIC
SAP Digital Business Service China
Hands on
Concur

550
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Section Exam
Section Exam
Section Exam
Semester Recap and Outlook
Lecture: SAP Solution
Overview in the Digital Age
2 hours
Lecture : T he Digital Core
Next Generation ERP ± S/4
HANA
2 hours
Hands - On
S/4 HANA ± Sim ple Finance
2 hours
Hands - On
S/4 HANA ± Sim ple Logistics
2 hours
Lecture : T he Business
Netw orks
SAP SaaS Applications
2 hours
Hands - On
SuccessFactors
2 hours
Hands - On
Custom er Engagem ent Cloud
2 hours
Lecture : System of Innovation
± SAP Leonardo
Introduction of Leonardo
2 hours
Hands - On
Leonardo Machine Learning
2 hours
Hands - On
Leonardo UX/Mobile
2 hours
Hands - On
Leonardo Big Data
2 hours
Hands - On
Leonardo IoT
2 hours
Lecture : Agile Implementation
Introduction of SAP Activate and
Solution Manager
2 hours
Lecture : Leonardo Innovation
Jumpstart
Introduction of Design T hink ing
2 hours
Hands - On (group work )
Design T hink ing
4 hours
Hands - On (group work )
Conceptual Prototype
4 hours
Hands - On (group work )
Realization via SAP Cloud
Platform
8 hours
Hands - On (group work )
Presentation of Final Result
4 hours
Lecture : T he New Platform
HANA Overview
2 hours
Hands - On: HANA Deep dive 1
Basic Modelling
2 hours
Hands - On: HANA Deep dive 2
AFL and PAL libraries
2 hours
Lecture: Case Studies 1
HANA Innovation Show Case 1
2 hours
Hands - On
Leonardo Analytics
2 hours
Lecture: Case Studies 2
HANA Innovation Show Case 2
2 hours
Lecture : SAP Cloud Platform
Introduction of Cloud Platform
2 hours
Hands - On
Ariba
2 hours
Semester 1 ± System of Record Semester 2 ± System of Innovation
Hands - On
Solution Manager 7.2
2 hours
Section Exam
Section Exam
Notes:
1. Hands - on by
default is
supposed to be
covered by W PB
hands - on file.
2. In semester 2,
Beside design
thinking and final
presentation,
courses with
more than 2
hours will be
spited
Hands - On
Concur
2 hours
Lecture
Hands - On
Exam
Section Exam

551
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
ƒ Scenario
ƒ Exercises
± Travel Request
± Expense
Agenda

552
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Goals
This course will prepare you to learn u
‡ How to create a trip
‡ How concur T&E ensures greater policy compliance and gain
visibility with Reporting
‡ What kind of features does concur have

Scenario

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
This demo covers an end to end process of Integrated Travel and Expense scenario. The demo
lists the steps about how to create a trip, maintain travel preferences, expense a trip and highlights
how concur T&E ensures greater policy compliance and gain visibility with Reporting.
To streamline processes and gain control over spend, businesses of all sizes are automating the
management of their travel and expense programs to gain insight into their spending, improve
efficiencies, and reduce costs. Automation offers an efficient, consistent process, configured for
local differences. And with regulatory concerns and the need for cost control higher than ever, end -
to - end travel and expense management solutions provide the transparency required to monitor
compliance and track spend.
Demo Description

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Scenario
With &RQFXU ¶V mobile
application, you can
create, review and
approve expense reports
and book and change
your travel itinerary ±
hotels, airfare, taxis, rail
and rental cars ± all from
smartphone.
No more paper
Be mobile
All - in - one
Make it
simple
Concur pulls all the
pieces of travel and
expense
management together
into one system with
a simple, single sign -
on.
*Screenshots shown are for dem onstration purposes only and are not final product com mitments
Concur offers
electronic receipts
directly from airlines,
hotels, car rental
companies and taxis,
virtually eliminating the
need to track and
manage paper
receipts.
Quick expense
reports
Concur
automatically
populates your credit
card and travel
purchases into your
expense reports, so
completing them is
quick and easy.
Concur simplifies your
travel and expense
process by
automating and
managing travel
booking and expense
reporting in an easy -
to - use, end - to - end
system.

Exercise 1
Travel Request

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Travel Request (1/8)
Explanation
1. &OLFN³3URILOH´
2. &OLFN³3URILOH6HWWLQJV´
3. &KRRVH³6HWXS7UDYHO$VVLVWDQWV´

558
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Travel Request (2/8)
Explanation
1. Admin, Ursula is your assistant,
&OLFN³6DYH´
2. &OLFN³&RQFXU´WREDFNWRWKHKRPH
page.
3. Fill out the travel information, such
as Destination, Departure Time,
Return Time, Airport pick off, Hotel,
HWFDQGWKHQ&OLFN³6HDUFK´WRJHW
the search result.

559
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Travel Request (3/8)
Explanation
1. &KRRVHWKHVRUWRUGHUE\³3ROLF\ ±
0RVW&RPSOLDQFH´
2. Choose the first option, and Click
³6KRZGHWDLOV´

560
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Travel Request (4/8)
Explanation
1. Try to choose the second option,
&OLFN³6HOHFW´
2. There is an alert said that it was
not in compliance with the travel
UXOHVR&OLFN³&DQFHO´
3. Then we choose the first option.

561
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Travel Request (5/8)
Explanation
1. Make sure we are clear about the
information of the ticket, then click
³5HVHUYH)OLJKWDQG&RQWLQXH´
2. In the Car rental page, Click the
first option to move forward.

562
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Travel Request (6/8)
Explanation
1. Review Price Summary, then click
³5HVHUYH&DUDQG&RQWLQXH´
2. In the Hotel booking page, Click
WKH³*UHHQODEHO´RSWLRQ\RXSUHIHU
DQG&OLFN³6HOHFW´WRPRYHIRUZDUG
3. Review Price Summary, then click
³5HVHUYH+RWHODQG&RQWLQXH´

563
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Travel Request (7/8)
Explanation
1. Review Total estimated cost and
&OLFN³1H[W´
2. Review Trip Booking Information
DQG&OLFN³1H[W´
3. Then you can see your trip task
from the homepage, Click the trip
to get your Travel Itinerary.

564
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Travel Request (8/8)
Explanation
1. Review the travel Itinerary, and
³$SSURYH´WKHWUDYHO

Exercise 1
Expense

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Expense (1/10)
Explanation
1. ,QWKH³7UDYHO´WDESDJH\RXFDQ
find upcoming trips and view the
³([SHQVH´
2. Then we can see the expense
detail page, Click Hotel to deep
dive to the expense page.

567
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Expense (2/10)
Explanation
1. ³0LQLEDU0RYLH´LVSHUVRQDO
expense, so Click it and Click
³&DQFHO´WRUHPRYHIURPWKH
Expense.
2. &KRRVH³&DU5HQWDO´WKHUHLVDQ
DOHUWVKRZVWKDW³&RUSRUDWHSROLF\
is to refuel rental prior to drop off,
please enter comment as to why
\RXGLGQRWUHIXHO´
3. Then Type in comment.
4. Click ³ Save ´ to save the notes ož

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PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Expense (3/10)
Explanation
1. &OLFN³( - 5HFHLSW´
2. 7KHQ&OLFN³4XLFN([SHQVHV´
3. Filled out some quick expenses
DQGWKHQ&OLFN³6DYH´

569
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Expense (4/10)
Explanation
1. For Dues/Membership Fees, Click
³$YDLODEOH5HFHLSWV´:HFDQ
check uploaded receipts.
2. Click

570
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Expense (5/10)
Explanation
1. For Dues/Membership Fees, Click
³$OORFDWH´WR$OORFDWHWKLVIHHWR
different
2. &OLFN³6DYH´WRILQLVKWKHDOORFDWLRQ

571
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Expense (6/10)
Explanation
1. Click ³ Business Meal(attendees) ´
to create a new expense of
business meal.
2. &OLFN³$GG´WRDGGDWWHQGHHVRIWKH
meal.
3. ³)DYRULWHV´FRQWDLQVDWWHQGHHV
collected.
4. Choose the attendee, then Click
³$GGWR([SHQVH´WRVDYH

572
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Expense (7/10)
Explanation
1. Click ³ Personal Car Mileage ´ to
create a new expense of Personal
Car Mileage.
2. 7KHQ2SHQWKH³0LOHDJH
&DOFXODWRU´

573
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Expense (8/10)
Explanation
1. Fill out needed information to
calculate the personal car mileage
and cost.
2. &OLFN³$GG0LOHDJHWR([SHQVH´
3. &OLFN³9LHZ5HLPEXUVHPHQW5DWHV´
to see how much you can get per
mile, then Click Save.

574
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Expense (9/10)
Explanation
1. )LQDO5HYLHZ&OLFN³$FFHSW
6XEPLW´WRVXEPLWWKHH[SHQVH
2. Then go back to homepage, Click
³$SSURYDOV´

575
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Expense (10/10)
Explanation
1. Click the report you want to check.
2. <RXFDQFKHFNHDFKLWHP¶VUHFHLSW
and expense.
3. &OLFN³$SSURYH´WRDSSURYHWKH
expense.

576
PUBLIC© 2017 SAP SE or an SAP affi l i ate company. Al l ri ghts reserved. Ä
Course Summary
You should now be able to:
9 Create a Trip Request with compliance
9 Create an Expense Request

Thank you.

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