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PMLE Practice Question: Drag and drop the steps to set up a feature store…
Drag and drop the steps to set up a feature store for ML features using Vertex AI Feature Store in the correct order.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Define entity type and features, then ingest data, then serve, then monitor.
The correct sequence to set up a feature store using Vertex AI Feature Store is: first define the entity type and its features (schema), then ingest feature data into the store, then serve those features to models for predictions, and finally monitor the store for data quality, freshness, and drift. This ensures a logical flow from definition to consumption to observability.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Define entity type and features, then ingest data, then serve, then monitor.
Why this is correct
This is the correct order because you must first define the schema (entity type and features) before you can ingest data. After ingestion, you serve the features for online or batch predictions, and finally monitor for performance and drift.
- ✗
Ingest data, then define entity type and features, then serve, then monitor.
Why it's wrong here
This is incorrect because you cannot ingest data before defining the entity type and features – the ingestion process requires the schema to be defined first.
- ✗
Define entity type and features, then serve, then ingest data, then monitor.
Why it's wrong here
This is incorrect because you must ingest data before serving features – serving without ingested data would return empty or stale results.
- ✗
Monitor, then define entity type and features, then ingest data, then serve.
Why it's wrong here
This is incorrect because monitoring is the final step; it cannot be performed before the feature store is set up and data is served.
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