The final review mixes the course's SQL and operational decisions. Each fictional team has a constraint that changes the answer: a fixed reporting grain, late updates, a scan allowance or an evaluation window. Choose the response that meets the whole requirement.
A correct feature name isn't enough. A partition filter can reduce the data read without proving that the final aggregation is at the right grain. A model can fit its training rows while failing on new observations. Treat the distractors as possible workplace mistakes, and use the explanation to identify what evidence you would collect before putting the design into service. These questions review earlier lessons and introduce no additional cloud controls.