Which of the following is not a valid reason to use partial runs when developing a workspace?

• A. Using incremental development to test each section of your workspace as it is built.
• B. Avoiding slow workspace development waiting to read in source data on every run.
• C. Feature caching mode automatically detects changes in schema for you and issues a warning.
• D. You can save caches with a template to share with colleagues while troubleshooting or validating workflows.

Answer: (C)

Partial runs are all about speeding up development by focusing on a portion of the workspace and reusing work that’s already been done, so you can test ideas incrementally and avoid re-reading large source datasets on every run. This makes it easy to verify each section as you build it, reduces wait time between iterations, and lets you share useful cached results with teammates for troubleshooting or workflow validation.

The option describing a caching mode that automatically detects schema changes and issues a warning isn’t a direct benefit of using partial runs. That capability belongs to how caches are managed and validated, not to the practice of running only parts of a workspace. Relying on automatic schema-change detection can be unreliable when using partial runs, since caches may become stale if the schema changes, and you’d still need to invalidate and rebuild caches to ensure correctness. So this capability isn’t a reason to adopt partial runs.