Read Data from ADLS Gen2 and Load into Lakehouse Table Using Pipeline | Microsoft Fabric Tutorial

Read Data from ADLS Gen2 and Load into Lakehouse Table Using Pipeline

Microsoft Fabric Tutorial

📘 Overview

In this tutorial, you’ll learn how to build a scalable ingestion pipeline in Microsoft Fabric that reads structured data from Azure Data Lake Storage Gen2 (ADLS Gen2) and loads it into a Lakehouse Table.

✅ Topics Covered

• How to create a pipeline that connects to ADLS Gen2
• How to configure Lakehouse Table as the destination
• How to map and transform schema as part of the pipeline
• Practical demonstration of moving structured data into a Delta Table
• Best practices for building scalable ingestion workflows

⚙️ Step-by-Step Instructions

1. Create a new pipeline in Microsoft Fabric workspace.
2. Use the Copy Activity to link your ADLS Gen2 container as the source.
3. Choose a Lakehouse Table as the destination and select or create your Delta Table.
4. Use the Mapping tab to map source columns to target table columns.
5. Apply any required transformations such as renaming columns, changing data types, or trimming values.
6. Run the pipeline and verify data was successfully written to the Lakehouse Delta Table.

💡 Best Practices

• Use dynamic file paths if you're working with partitioned data.
• Enable fault tolerance and retry logic in your pipeline for production workflows.
• Validate column data types and schema compatibility before loading.
• Use Lakehouse staging zones before merging into production tables.

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