A Complete SAS Tutorial – Learn Advanced SAS Programming in 10 Mins

Today, we will start a new journey of SAS technology with the help of a comprehensive SAS tutorial.

There are various questions which arise in our mind when we see the word ‘SAS’ like, What is SAS? Where it is used? What is the future scope in technology? You will get all the answers for such similar questions in this SAS tutorial.

1. A Complete SAS Tutorial –
Learn Advanced SAS
Programming in 10 Mins

2. Today, we will start a new journey of SAS technology with the help of a
comprehensive SAS tutorial.
There are various questions which arise in our mind when we see the word
‘SAS’ like, What is SAS? Where it is used? What is the future scope in
technology? You will get all the answers for such similar questions in this SAS
tutorial.
Let’s quickly start by exploring the basic concept of SAS programming.
Introduction to SAS Programming
We require some statistical tools to handle the tonnes of data generated each
day. Structuring and analyzing the data is the main task, followed by strategic
decision making. It can be directly said that the cause and excess of data, led
to the efficient generation of data analysis tools like SAS.
SAS Programming Language is defined as the science of data-driven decision
making. Technology can bring us from raw data to structured readable data; it
even predicts many solutions to a problem.
But it is ultimately the call of humans to make the final decision. It uses the
repetitive and procedural exploration of past data to handle business
decisions.
Let’s understand this with an example, have you ever wondered, why is a
billing point at the mall, loaded with gum and candies on its sides.

3. This is not an unplanned move, rather a strategically made decision. Let’s see
how, for instance when parents are at the billing counter with their kids,
waiting for their turn. The gums and candies lure the kids and they demand of
having it.
To prevent creating a scene at the counter, the parents have to unwillingly buy
it. This results in an increased sale of candies and gum. This is what business
analytics does, observes the trends and patterns and mould the business
accordingly to make a profit.

4. Chocolate Display Counter
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What is SAS Programming?
SAS stands for ‘Statistical Analysis Systems’. It can be dated back to 1970s, a
software tool developed by SAS Institute. It is a closed source analysis tool. A
widely used analysis tool in the corporate world to make strategic decisions.
A fun fact, SAS was used originally for statistics application in agriculture
projects. But now it’s used in various industries from media to retail,
education, and finance, etc.
In simple words, SAS Programming allows you to process a large chunk of raw
data to manageable small sets of data, leading to results which help in decision
making.

5. Processing of Raw Data
Components of SAS Programming
Now in SAS Tutorial, we will learn components of SAS Programming
Language:
i. Base SAS
It is a basis for all SAS software. SAS has hardware agility and integrates into
any computer environment. It is easy to learn and is not code intensive. It
provides data ease in data readability and interpretation.
ii. SAS/GRAPH

6. It a data visualization technique. It helps represent structured data into graphs
by enhancing the process of interpretation.
iii. SAS/STAT
It helps us perform various statistical analysis variance, regression, and
psychometric analysis. Some statistical techniques like such as ANOVA
procedures are specially strung in the SAS environment.
iv. SAS/ETS
It is specially used for forecasting and for the time series analysis.
v. SAS/IML
IML is called Interactive Matrix Language. It is used to translate mathematical
formulas into an innovative program for matrix computation and
optimization.
vi. SAS/INSIGHTS and Enterprise Miner
SAS/INSIGHTS and Enterprise Miner are used for data mining.

7. Building Blocks of SAS
Programming
This part of the SAS Tutorial covers, the technical part of SAS Programming.
DATA and PROC are two major building blocks of SAS Programming
Language. DATA helps to build a data set. The PROC refers to a Procedure. It
processes the data.
Now, for instance, consider if I wish to convert $ into Rs. So, if I use SAS for
this conversion, then the DATA converts dollars to rupees and creates a
dataset named ‘currency’. The PROC will print the result for us.
Statements are made up of PROC and DATA steps. DATA steps are
responsible to read data, on the other hand, PROC steps are used to perform
utility functions, analysis of data, or print reports.

8. Writing DATA and PROC steps

Results obtained

9. Features of SAS Programming
Language
SAS Programming as a tool is very helpful for analytics. SAS is software which
works in three simple processes. It gets data from various sources, cleans it
and processes it. SAS programming language is one of the easiest procedural
languages.
It has a simple syntax and various inbuilt libraries containing enormous
features. For instance, it has features like plotting graphs, finding
permutations and combinations and solving regression.

i. SAS Programs
●​They are a series of statements that execute in the set sequence.
●​SAS statements are simple instructions that communicate a
message.

10. ●​We can understand a SAS program with a bank example. For
instance, if we go to an atm to withdraw money, we have to provide
various kinds of information to the machine and then we get the
money.
ii. SAS Statements
●​All the SAS statements end in a semicolon. This is a basic rule that
differentiates a simple English statement from SAS statement.
●​These statements can be in upper or lowercase
●​Statements can continue on the next line.
●​Statements can start in any column.
●​A statement can be on the same line as other statements.
iii. Errors in SAS Programming
Errors in SAS occur mainly due to a missing semi-colon and misspelled words.
We can see these errors in red color in the log window.
SAS Windows
Initially, the SAS window was the same for all operating systems. But now
with changing time, SAS window looks different on different operating
systems like Windows, MAC, etc.
This provides a scope for customization of the SAS environment. However,
there are many common elements in various operating environments.
Now, in SAS Programming Tutorial, we will cover the SAS Windows in detail:
i. Editor

11. This is a text editor window to type, edit and submit SAS programs and also
process raw data files. Its features vary according to different versions and
operating environment.
ii. Log
After submission, various notes, error, etc. are displayed here. Even it provides
warnings with program statements here.
iii. Output
It provides the printable versions of our results here.
iv. Results
The result window shows a table of contents for our output window; we can
see a list of results in an outline format.
v. Explorer
This window acts as a shortcut to reach SAS files and libraries.

12. Data Libraries in SAS Programming
We can understand it with a very basic example. Before you make tea, it is
important for you to know where are all the ingredients? SAS Programming
libraries are the location where the SAS data sets are stored. The format of
SAS libraries depends mostly on the operating environment.
This is one of the best features of SAS Programming. Availability of various
libraries makes it very easier to perform a statistical function. In the new SAS,
studio libraries are present in the navigation panel.

13. Various inbuilt libraries in SAS Programming Language.
We can download the university SAS edition from sas.com
SAS Application
In the field of analytics, SAS major application lies in observing trends,
decipher patterns and provide statistical inferences. In the domain of data
management, it mainly contributes to a listing, characterizing, sorting and
filtering data.
Its application in the multivariate analysis includes factor analysis, preference
analysis and other various kinds of analysis. The crux of using SAS is to
analyze data, on which decisions can be made strategically.

14. Future Scope in SAS
SAS Programming Language has been in existence prior to R and Python. The
analytics market has acquainted itself with SAS very well now. It is a widely
used analytical tool, with a plethora of predictive packages, owing to it’s easy
to go programming syntax.
It is famous for the non- programming community too. Statistics show that
70% of analytics jobs are in SAS Programming, followed by R and then
Python. Its ever-evolving features according to industry needs is one major
factor in its favor.
SAS v/s R v/s Python

15. SAS Programming is one of the oldest tools used for analysis. But over time
many other tools have come into the market.
Commonly used data analysis software is SPSS, R, MATLAB, Rapid Miner,
Weka, SAP, Minitab, Apache Mahout, Statistica, etc. This section will mainly
focus on a comparison between SAS, R, and Python.
i. Cost and Availability
●​SAS
SAS being the closed source is quite expensive. It is professionally available if
the company has bought access.
●​R Programming
R programming is an open source software and is available free of cost in its
entire version.
●​Python
Similarly, python is an open source software and it is available free of cost in
its entire version.

ii. Ease of learning
●​SAS

16. It is very easy to learn, it also provides a GUI for non- programming
community. A huge database consisting of books, tutorials, videos, etc. are
readily available.
●​R Programming
R requires you to have a thorough understanding of coding. It is low-level
programming and requires a string coding hand.
●​Python
It is one of the simplest programming languages. It lacks a GUI for ease of
non-programmers.
iii. Graphical Capabilities
●​SAS
It has functional graphical support but fails to provide any customization. A
student needs to have a thorough knowledge of various graphical packages.
●​R Programming
R has advanced graphical features. This makes it easy for intense and
diversified graphical implications and inferences.
●​Python
Python has advanced graphical features. This makes it easy for intense and
diversified graphical implications and inferences.
iv. Improvisation in tools

17. ●​SAS
SAS gives out its new features in every new version. It releases it in closed
space, so these are well tested by experts. However, there is no new updating
every now and then.
●​R Programming
As R is an open source, it is updated quickly on a frequent basis. However, due
to open access, it is even prone to more errors.
●​Python
As Python is an open source, it updates quickly on a frequent basis. However,
due to open access, it is even prone to more errors.
v. Customer support and guidance
●​SAS
It is very high and established. Being a closed source, all your problems are
handled professionally.
●​R Programming
R is open source there lacks quality in customer care segment. But it has
online communities that can help you.
●​Python
Python is open source due to which it lacks in customer care segment. But it
has online communities that can help you.
So, this was all about the SAS Tutorial. Hope you like our explanation.

18. Summary
We studied SAS programming which is a statistical language for mining and
converting raw data into a legible and interpretable format. We use it in
business analytics to make strategic decisions. SAS program is sequential
statements, that we write in an orderly manner.
We can write SAS statements easily in English statements to instruct the
system. In short, we studied a complete guide or a cheat sheet for the SAS
Programming Tutorial.

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