You want to use a pipeline to copy data to a folder with a different name for each run. Which approach should you take?

You want to use a pipeline to copy data to a folder with a different name for each run. Which approach should you take?

• A. Create multiple pipelines - one for each folder name
• B. Use a Dataflow (Gen2)
• C. Add a parameter to the pipeline and use it to specify the folder name for each run
• D. Hard-code the folder name in the pipeline

Answer: (C)

The idea being tested is making a pipeline flexible by parameterizing the destination rather than fixing it hard. By adding a parameter for the folder name and using that parameter to determine where the data is written, you can run the same pipeline multiple times with different outputs. This keeps one reusable workflow, reduces duplication, and makes it easy to automate by passing the desired folder name at run time. Why this approach fits best: you can trigger the pipeline with any folder name and have the sink or destination path reference the parameter. This gives per-run customization without creating new pipelines or editing code, which is essential for scalable, repeatable data operations. Why the other options aren’t as good: creating multiple pipelines would duplicate logic and require maintenance across many pipelines whenever you need a new folder name. Hard-coding the folder name eliminates flexibility entirely and forces you to modify the pipeline for every new run. Using a Dataflow (Gen2) isn’t necessary for simply routing output to a folder; it adds complexity without addressing the per-run naming requirement.

The idea being tested is making a pipeline flexible by parameterizing the destination rather than fixing it hard. By adding a parameter for the folder name and using that parameter to determine where the data is written, you can run the same pipeline multiple times with different outputs. This keeps one reusable workflow, reduces duplication, and makes it easy to automate by passing the desired folder name at run time.

Why this approach fits best: you can trigger the pipeline with any folder name and have the sink or destination path reference the parameter. This gives per-run customization without creating new pipelines or editing code, which is essential for scalable, repeatable data operations.

Why the other options aren’t as good: creating multiple pipelines would duplicate logic and require maintenance across many pipelines whenever you need a new folder name. Hard-coding the folder name eliminates flexibility entirely and forces you to modify the pipeline for every new run. Using a Dataflow (Gen2) isn’t necessary for simply routing output to a folder; it adds complexity without addressing the per-run naming requirement.