In Fabric, which statement best describes the relationship between a Data Factory workload and Dataflow Gen2?

In Fabric, which statement best describes the relationship between a Data Factory workload and Dataflow Gen2?

• A. Data Factory is a workload where you can create a Dataflow Gen2 to transform data.
• B. Data Factory is not the place to create Dataflow Gen2 pipelines.
• C. Data Factory is primarily used for data visualization tasks.
• D. Data Factory can only copy data but cannot transform.

Answer: (C)

In Fabric, Data Factory acts as the workflow engine that orchestrates data workloads, while Dataflow Gen2 provides the transformation logic used inside a pipeline. The best description is that you can create and run a Dataflow Gen2 transformation as a step within a Data Factory pipeline to transform data during the workflow. This shows Data Factory isn’t limited to copying data or simply visual tasks; it can invoke Dataflow Gen2 to perform transformations as part of an end-to-end process. Visualization is handled by BI tools, not Data Factory, and Data Factory can do more than just copy—transformations can be integrated via Dataflow Gen2 within pipelines.

In Fabric, Data Factory acts as the workflow engine that orchestrates data workloads, while Dataflow Gen2 provides the transformation logic used inside a pipeline. The best description is that you can create and run a Dataflow Gen2 transformation as a step within a Data Factory pipeline to transform data during the workflow. This shows Data Factory isn’t limited to copying data or simply visual tasks; it can invoke Dataflow Gen2 to perform transformations as part of an end-to-end process. Visualization is handled by BI tools, not Data Factory, and Data Factory can do more than just copy—transformations can be integrated via Dataflow Gen2 within pipelines.