A retail company runs a nightly promotion campaign. Each night, they must generate personalized discount codes for all 2 million customers in their loyalty database. The codes are emailed the next morning, so results are not needed until the batch completes. The data science team wants the simplest solution that minimizes compute cost. Which model serving approach should they use?

Streaming serving with a micro-batch trigger every minute

Batch serving on the full customer dataset in a scheduled job

Realtime serving with a REST endpoint called from a scheduled job

Realtime serving with a single request containing all customer IDs

A company needs to generate a daily report of customer churn predictions for the entire customer base. Which serving approach is most appropriate?

Any of the three approaches would work equally well

In which scenario is batch model serving most appropriate?

Generating nightly churn-risk scores for all customers in a database

Providing a recommendation each time a user refreshes a web page

Returning a fraud score instantly when a credit card transaction is attempted

Scoring sensor readings the moment they arrive to trigger an alert

Which of the following is an advantage of batch model serving?

Can efficiently process very large datasets in a cost-effective manner

Provides the lowest possible latency for individual requests

Requires no infrastructure to run

Handles unbounded data streams with continuous processing

Which use case is best suited for realtime model serving?

Detecting anomalies in a live video feed as frames are captured

Generating a monthly report of sales forecasts

Approving or declining a loan application submitted through a web portal

Updating a recommendation model with new user data every hour

DatabricksCertified Machine Learning Associate

Domain 4Objective 1

Identify the Differences and Advantages of Model Serving Approaches: Batch, Realtime, and Streaming MACHINE-LEARNING-ASSOCIATE Practice Questions (Page 1)

Part of the Section 4: Model Deployment domain, which makes up ~30% of our current practice bank. Databricks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~11–18 in this domain), expect 2–3 from this objective — we provide 20 practice questions to prepare you well beyond it. (estimate)

20questions here

4free pages

8concepts

Questions 1–5

1application · medium
A retail company runs a nightly promotion campaign. Each night, they must generate personalized discount codes for all 2 million customers in their loyalty database. The codes are emailed the next morning, so results are not needed until the batch completes. The data science team wants the simplest solution that minimizes compute cost. Which model serving approach should they use?
Select an answer first
2foundation · easy
A company needs to generate a daily report of customer churn predictions for the entire customer base. Which serving approach is most appropriate?
Select an answer first
3foundation · easy
In which scenario is batch model serving most appropriate?
Select an answer first
4foundation · easy
Which of the following is an advantage of batch model serving?
Select an answer first
5foundation · easy
Which use case is best suited for realtime model serving?
Select an answer first

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