Azure Data Factory Tutorial: A Detailed Explanation For Beginners

Azure Data Factory (ADF) is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data at scale, without writing extensive custom code.

Core Components

• Pipelines — logical grouping of activities that perform a unit of work
• Activities — individual processing steps such as copy, transform, or execute
• Datasets — pointers to the data you want to use in an activity
• Linked Services — connection information to external resources like databases or storage
• Integration Runtime — the compute infrastructure that executes the activities

Building a Basic Pipeline

• Create linked services for your source and destination
• Define datasets that represent the input and output data
• Add a Copy Data activity to move data between the two
• Set a trigger to run the pipeline on a schedule or in response to an event

Why Teams Use ADF

• Serverless, pay-for-what-you-use pricing model
• Over 90 built-in connectors to popular data sources
• Visual, code-free pipeline authoring with the drag-and-drop UI
• Native integration with Azure Synapse, Databricks, and Azure Functions