Scheduled Workflows in Databricks are designed to run at specified intervals, and the associated clusters are started only when the workflow is triggered. This approach minimizes resource consumption and costs because the cluster terminates after the job completes. Option A is incorrect because always-running clusters are not required for scheduled workflows. Option B describes streaming/continuous processing, not scheduled batch workflows. Option D incorrectly implies workflows run continuously, which applies to streaming jobs, not scheduled ones.