Databricks Certified Machine Learning Professional — Question 9

A machine learning engineer needs to deliver predictions of a machine learning model in real-time. However, the feature values needed for computing the predictions are available one week before the query time.
Which of the following is a benefit of using a batch serving deployment in this scenario rather than a real-time serving deployment where predictions are computed at query time?

Answer options

• A. Batch serving has built-in capabilities in Databricks Machine Learning
• B. There is no advantage to using batch serving deployments over real-time serving deployments
• C. Computing predictions in real-time provides more up-to-date results
• D. Testing is not possible in real-time serving deployments
• E. Querying stored predictions can be faster than computing predictions in real-time

Correct answer: E

Explanation

The correct answer is E because querying pre-computed predictions stored from batch processing is generally quicker than generating predictions on-the-fly at query time. Options A, B, C, and D do not present valid benefits for batch serving in this context; they either misrepresent capabilities or do not apply to the scenario's constraints.