Welcome to another insightful Azure Data Factory (ADF) tutorial! In this video, we’ll take a deep dive into one of the most powerful features of the Copy Activity—how to add Additional Columns dynamically or statically during data movement. This feature enables you to enhance your datasets with metadata or custom values while seamlessly transferring data between source and destination.

📌 What You’ll Learn:
Introduction to Additional Columns in ADF

Overview of the Additional Columns feature.
When and why you should use it.
Configuring Additional Columns in Copy Activity

Adding static values to your data (e.g., source system, batch ID).
Using dynamic expressions for additional columns (e.g., timestamps, pipeline run IDs).
Practical Use Cases

Adding a timestamp column to track data transfer times.
Including pipeline metadata (like RunID or Execution Date) for auditing purposes.
Creating batch identifiers for incremental loads.
Step-by-Step Demonstration

Setting up a Copy Activity with Additional Columns.
Writing expressions to dynamically populate column values.
Validating results in the destination dataset.
Best Practices and Tips

Ensuring data consistency with additional columns.
Optimizing performance when using dynamic expressions.
Troubleshooting Common Issues

Debugging incorrect column values.
Handling data type mismatches.

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