Azure Data Factory (ADF) is a cloud-based data integration service that allows users to create, schedule, and manage data pipelines. ADF enables the movement of data between various sources and destinations, including on-premises, cloud-based, and hybrid environments. With ADF, users can build complex data pipelines that can process, transform, and move data at scale.
Accessing a Source and Target System in ADF
To start building data pipelines in ADF, you first need to create a linked service to the data source and target. A linked service is a connection between ADF and an external data store. ADF supports a wide range of data stores, including Azure SQL Database, Azure Blob Storage, and Amazon S3.
To create a linked service, you need to provide the connection details for the data source or target. This can include things like the server name, database name, username, and password. Once the linked service is created, you can use it to connect to the data source or target in your ADF pipeline.
Creating a Data Set in ADF
A data set is a reference to the data that you want to process in your pipeline. A data set defines the format, location, and structure of the data. You can create a data set for a file, a table, or a folder.
To create a data set in ADF, you need to specify the source or target data store, the data format, and the location of the data. You can also define the schema and partitioning of the data set.
Creating a Pipeline in ADF
A pipeline is a collection of activities that define the flow of data in your ADF solution. Activities are the building blocks of a pipeline and can include things like data transformation, data flow, and control flow.
To create a pipeline in ADF, you need to define the activities and their dependencies. You can also specify the order in which the activities should be executed and any conditions that need to be met before the activity can run.
Executing an ADF Copy Activity
A copy activity is a type of data movement activity that allows you to copy data from a source data store to a destination data store. You can use the copy activity to move data between different data stores, transform the data, and apply data mapping.
To execute an ADF copy activity, you need to select the source and destination data sets, the linked services, and any transformations or mappings that need to be applied to the data. Once the copy activity is configured, you can run it to move the data from the source to the destination.
Get Started with ADF Today
If you’re interested in learning more about Azure Data Factory, we offer a free one-hour course that covers the basics of ADF. Our course will teach you how to create and manage data pipelines in ADF, as well as how to use ADF to move and transform data between different data stores. Sign up for our free course today and start building data pipelines with Azure Data Factory.
