Azure Data factory notes for beginners in ETL

Azure data factory notes

1. © 2022 databag.ai - Proprietary and Confidential

2. What is Azure Data Factory - ADF ?

+ Itis the cloud-based ETL and data integration service that allows you to
create data-driven workflows for orchestrating data movement and
transforming data at scale. Using Azure Data Factory, you can create and
schedule data-driven workflows (called pipelines) that can ingest data from
disparate data stores.

You can build complex ETL processes that transform data visually with
data flows or by using compute services such as Azure HDInsight Hadoop,
Azure Databricks, and Azure SQL Database.

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3. ETL - Extract Transform Load

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4. ELT - Extract Load Transform

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25. Top-level concepts - ADF

Azure Data Factory is composed of below key components.

Pipelines

Activities

Datasets

Linked services

Data Flows
Integration Runtimes
Triggers

These components work together to provide the platform on which you can compose
data-driven workflows with steps to move and transform data.

© 2022 databag al - Proprietary and Confidential

26. Pipeline

A data factory might have one or more pipelines. A pipeline is a logical grouping of
activities that performs a unit of work. Together, the activities in a pipeline perform a
task.

Example {A pipeline can contain a group of activities that ingests data from an Azure

blob, and then runs a Hive query on an HDInsight cluster to partition the data. Y

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27. Activity

Activities represent a processing step in a pipeline. For example, you might use a copy
activity to copy data from one data store to another data store.

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32. Top-level concepts - ADF

Azure Data Factory is composed of below key components.

Pipelines
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Integration Runtimes~
Triggers_

These components work together to provide the platform on which you can compose
data-driven workflows with steps to move and transform data.

© 2022 databag ai - Proprietary and Confidential

33. Pipeline

A data factory might have one or more pipelines. A pipeline is a logical grouping of
activities that performs a unit of work. Together, the activities in a pipeline perform a
task.

Example - A pipeline can contain a group of activities that ingests data from an Azure
blob, and then runs a Hive query on an HDinsight cluster to partition the data.

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45. Datasets and Linked services

Datasets represent data structures within the data stores, which simply point to or
reference the data you want to use in your activities as inputs or outputs.

Linked services are much like connection strings, which define the connection
information that's needed for Data Factory to connect to external resources. Think of
it this way: a linked service defines the connection to the data source, and a dataset
represents the structure of the data. For example, an Azure Storage-linked service
specifies a connection string to connect to the Azure Storage account. Additionally, an
Azure blob dataset specifies the blob container and the folder that contains the data.

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46. Datasets and Linked services

Datasets represent data structures within the data stores, which simply point to or
reference the data you want to use in your activities as inputs or outputs.
——— ni

ked services are much like connection strings\which define the connection
information that's needed for Data Factory to connect to external resources. Think of
it this way: a linked service defines the connection to the data source, and a dataset
represents the structure of the data. For example, an Azure Storage-linked service
specifies a connection string to connect to the Azure Storage account. Additionally, an
Azure blob dataset specifies the blob container and the folder that contains the data.

© 2022 databag ai - Proprietary and Confidential

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49. Integration Runtime

In Data Factory, an activity defines the action to be performed. A linked service
defines a target data store or a compute service. An integration runtime provides the
bridge between the activity and linked Services. It's referenced by the linked service
or activity, and provides the compute environment where the activity either runs on
or gets dispatched from. This way, the activity can be performed in the region closest
possible to the target data store or compute service in the most performant way
while meeting security and compliance needs.

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50. Integration Runtime

In Data Factory, an activity defines the action to be-performed. A linked service
defines a target data store or a compute service\An integration runtime provides the
bridge between the activity and linked Services. js referenced by the linked service
or activity, and provides the compute environment where the activity either runs on
or gets dispatched from. This way, the activity can be performed in the region closest
possible to the target data store or compute service in the most performant way
while meeting security and compliance needs.

© 2022 databag al - Proprietary and Confidential

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53. Triggers

Triggers represent the unit of processing that determinesjwhen a Pipeline execution

needs to be kicked off. {here are different types of triggers for different types events.

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58. Create First Azure Data Factory Pipeline

Create ADF Instance

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129. Integration Run Time

Integration runtime is the Compute infrastructure]used by Azure Data Factory (ADF)
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© 2022 databag ai - Proprietary and Confidential

130. Types of Integration Run Times

= Azure integration runtime
= Self-hosted integration runtime

= Azure-SQL Server Integration Services (SSIS)
integration runtime

© 2022 databag ai - Proprietary and Confidential

131. Types of Integration Run Times

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136. Integration runtime setup

Integration runtimes Network environment: -

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137. Choose the network environment of the data source / destination or external compute to which the
integration runtime will connect to for data flows, data movement or dispatch activities:

Azure

Use this for running data flows, data movement, external and pipeline activities
in a fully managed, serverless compute in a
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Self-Hosted
Use this for running data movement, external and pipeline activities in an on:

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self-hosted integration runtime to stage the data on cloud storage and then use
data flows to transform it.

View less À

External Resources:

138. Choose the network environment of the data source / destination or external compute to which the
integration runtime will connect to for data flows, data movement or dispatch activities:

Azure

Use this for running data flows, data movement, external and pipeline activities
in a fully managed, serverless compute in ey
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Use this for running data movement, external and pipeline activities in an on-

premises / private network by installing the integration runtime

Note: Data flows are only supported on Azure integration runtime. You can use
self-hosted integration runtime to stage the data on cloud storage and then use
data flows to transform it.

View less À

External Resources:

139. Choose the network environment of the data source / destination or external compute to which the
integration runtime will connect to for data flows, data movement or dispatch activities:

Azure

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premises / private network by installing the integration runtime

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self-hosted integration runtime to stage the data on cloud storage and then use
data flows to transform it )

View less ~

External Resources:

140. Choose the network environment of the data source / destination or external compute to which the
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External Resources:

141. Choose the network environment of the data source / destination or external compute to which the
integration runtime will connect to for data flows, data movement or dispatch activities:

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162. Integration runtimes

Integration runtime setup

In Runtime isthe native compute used to execute or dispatch activities. Choose what
tegration runtime to create based on required capabilities. Learn more Ü

Azure, Self-Hosted

Perform data flows, data movement and dispatch activities to external compute

Azure-SSIS
Lft-and-shift existing SSIS packages to execute in Azure.

163. Types of Integration Run Times

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164. Types of Integration Run Times

© 2022 databag al - Proprietary and Confidential

165. Types of Integration Run Times

© 2022 databag ai - Proprietary and Confidential

166. Types of Integration Run Times

© 2022 databag ai - Proprietary and Confidential

167. In-depth understanding of Pipeline and Activity

A data factory might have one or more pipelines. A pipeline is a logical
grouping of activities that performs a unit of work

Activities represent a processing step in a pipeline for example either
consume or produce data

© 2022 databag al - Proprietary and Confidential

168. In-depth understanding of Pipeline and Activity

A data factory might have one or more pipelines. A pipeline is a logical
grouping of activities that performs a unit of work

Activities represent a processing step in a pipeline for example either
consume or produce data

© 2022 databag ai - Proprietary and Confidential

169. Types of Activities

= Data movement activities

= Data transformation activities

= Control flow activities

© 2022 databag ai - Proprietary and Confidential

170. Types of Activities

= Data movement activities _
= Data transformation activities _

= Control flow activities

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