Which statement accurately describes how a Data Factory workflow interacts with a Dataflow Gen2 when loading data into a lakehouse?

• A. Data Factory is not involved in lakehouse loading when using Dataflow Gen2.
• B. You can only use Data Factory to copy data, not transform with Dataflow Gen2.
• C. Data Factory can use a Dataflow Gen2 to transform data and then load it into a lakehouse.
• D. Data Factory automatically runs Spark jobs for Dataflow Gen2 transformations.

Answer: (C)

Data Factory pipelines can orchestrate both movement and transformation, and Dataflow Gen2 fits right into that flow. You can take data from a source, apply graphical transformations with a Dataflow Gen2 activity, and then write the transformed results into a lakehouse located in your data lake (for example, a Delta Lake-style lakehouse). This integrated approach means the transformation and the load to the lakehouse happen as part of a single pipeline, leveraging Data Factory to manage the end-to-end process.

The other statements don’t reflect how the two services work together: Data Factory isn’t just a passive loader, and Dataflow Gen2 isn’t limited to copying data without transformation. While Dataflow runs on Spark under the hood, the important takeaway is that you can transform data with Dataflow Gen2 and then load it into a lakehouse within the same workflow.