Javatpoint Azure Data Factory ((hot))

Understanding Azure Data Factory: A Comprehensive Guide (Inspired by Javatpoint)

Data Movement: Copy Activity (movement from source to sink).
Data Transformation: Stored Procedure, Databricks Notebook, HDInsight Hive, or Data Flow.
Control Flow: ForEach, If Condition, Wait, Until, Execute Pipeline.

Debug: Run once for testing.
Add Trigger: Schedule (e.g., run daily at 2 AM) or Tumbling Window (for finance backfills).

"activities": [ "name": "Lookup Last Date", "type": "Lookup" , "name": "Incremental Copy", "type": "Copy", "source": "query": "SELECT * FROM Orders WHERE OrderDate > '@activity('Lookup Last Date').output.firstRow.LastRunDate'" , "name": "Update Watermark", "type": "SqlServerStoredProcedure" ]

Pipelines: Combine activities, set dependencies, and control flow.