Microsoft Fabric brings together data integration, data engineering, data warehousing, analytics, and business intelligence in a unified platform. Data Factory in Microsoft Fabric provides capabilities for connecting, moving, and transforming data across different data sources. In this beginner-friendly course, we focus specifically on Data Pipelines in Microsoft Fabric Data Factory. Rather than trying to cover every feature available in Data Factory, this course takes a focused, hands-on approach. You will build a practical data ingestion solution that moves files from Azure Data Lake Storage Gen2 (ADLS Gen2) into a Microsoft Fabric Lakehouse.
What will you learn?
We start by setting up the resources required for our project. You will create the necessary Azure resources and storage services and then move into Microsoft Fabric to create a Workspace and Lakehouse. Once the environment is ready, you will create your first Microsoft Fabric Data Pipeline. We begin with a simple use case: copying a single file from Azure Data Lake Storage into the Fabric Lakehouse. You will configure the source and destination, execute the pipeline, and validate the output. After understanding the basic Copy activity, we gradually make the pipeline more dynamic. You will use the Get Metadata activity to retrieve information about files available in Azure Data Lake Storage. This allows our pipeline to discover files rather than depending entirely on manually specified file names.
