fabric-data-factory

To orchestrate scalable data ingestion in Microsoft Fabric, use Data Factory pipelines to coordinate Copy Activity and Dataflows Gen2. This approach provides best-practice configurations for reliable data workflows and structured transformation.

Structure a Fabric pipeline by ingesting data with Copy Activity, transforming it using a Dataflow Gen2, and orchestrating the sequence within a Pipeline. This end-to-end pattern aligns with Fabric documentation for scalable workflows.

Choose between Dataflows Gen2 and Copy Activity using decision guidance for tool selection. Dataflows Gen2 handles transformation logic, while Copy Activity manages scalable data ingestion within your Fabric orchestration pipeline.

Yes, Notebook Spark and Eventstreams are included in Fabric tool selection guidance. You can coordinate these components alongside Mirroring and Dataflows Gen2 within Pipeline orchestration for scalable data processing.

Yes, it provides example templates and best-practice configurations for Fabric Data Factory pipelines. These templates cover ingestion, transformation, and orchestration scenarios to reduce guesswork in data projects.

Dataflows Gen2 is optimized for transformation logic within orchestrated pipelines, but complex large-scale transformations may require Notebook Spark. Decision guidance helps determine when to use specific tools for your data scenarios.