"A cloud-based data integration service that allows you to create, schedule, and orchestrate data-driven workflows (called pipelines) to move and transform data from various sources to destinations like Azure Data Lake Storage, Azure Synapse Analytics, or SQL Database."
Cleanse and transform data into a usable format using activities like copy data, stored procedures, and mapping data flows. javatpoint azure data factory
Always connect your ADF to a Git repository (Azure DevOps or GitHub). "A cloud-based data integration service that allows you
| Feature | ETL (Extract, Transform, Load) | ELT (Extract, Load, Transform) | | :--- | :--- | :--- | | | Extract -> Transform -> Load | Extract -> Load -> Transform | | Transformation Location | Done on a separate engine (like Spark/Hive) before loading. | Done inside the destination data warehouse (like Synapse). | | ADF Role | ADF orchestrates the external transformation. | ADF moves raw data; transformation happens in the warehouse. | | Done inside the destination data warehouse (like Synapse)
"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" ]
This comprehensive guide covers everything you need to know about Azure Data Factory, aligning with the structured, easy-to-learn approach popularized by educational platforms like Javatpoint. What is Azure Data Factory (ADF)?