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Azure Data Factory is a cloud based integration service that allows to create
data driven workflows in the cloud for orchestrating and automating data
movement and data transformation
The aim of Azure Data Factory is to fetch data from one or more sources and
convert them into format that we process . It ingests data and load the data from
different sources .
It is a cloud based ETL that allow us to create data-driven pipelines for orchestrating
data movement and transforming data
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Top Level Concepts of Azure Data Factory
• Pipeline
• Activity
• Datasets
• Linked Services
• Triggers
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LINKED SERVICES
Linked Services can be found in Manage section of ADF section
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ACTIVITY
There are 3 types of activities
Data Movement Activities – This is basically only the Copy Activity
Data Transformation Activity
Control Flow Activity :
•to deal with variables (Append Variable, Set Variable and Filter)
•looping (ForEach and Until)
•branching (the If Condition activity)
•executing other pipelines with Execute Pipeline activity, or SSIS packages with Execute SSIS
Package activity.
•Handling metadata or reference data with the Get Metadata activity or the Lookup activity.
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Self hosted integration runtime as the name suggested, is the IR managed by you itself rather than azure. This will make
you responsible for the installation, configuration, maintenance, installing updates and scaling. Now as you host the IR , it
can access the on premises network as well.
Azure-SSIS Integration Runtimes
As the name suggested the azure-SSIS integration runtimes are actually the set of vm running the SQL Server Integration Services (SSIS
by Microsoft. Again the responsibility of the installation, maintenance, are of azure only. Azure Data Factory uses azure-SSIS integration ru
executing SSIS packages.
