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MLA-C01 Practice Question: A data scientist needs to create a feature group…
A data scientist needs to create a feature group in Amazon SageMaker Feature Store for real-time recommendations. Which TWO configurations are required? (Select TWO.)
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
✓
Specify a record identifier feature
Online store must be enabled for real-time serving, and a record identifier is required to uniquely identify records. Offline store and feature description are optional; time-to-live is not a standard feature.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable the offline store
Why it's wrong here
Enabling the offline store is optional; a feature group can be created with only the online store, so it fails the required-configuration test. It is tempting because offline storage supports training-data retrieval, and it would be correct when the same features must be reused for batch model training.
- ✗
Provide a feature description
Why it's wrong here
A feature description is optional metadata; the CreateFeatureGroup API does not require it, so it cannot satisfy the two mandatory configurations. It is tempting because documenting features aids discoverability, and it would be the correct choice when governance demands searchable definitions rather than a functioning online store.
- ✓
Specify a record identifier feature
Why this is correct
Every SageMaker Feature Store feature group requires a record identifier feature, which uniquely identifies each record and enables point-in-time lookups and upserts. Without it the feature group cannot be created, satisfying the stem's requirement for a mandatory configuration for real-time recommendations.
- ✗
Set a time-to-live (TTL) for the records
Why it's wrong here
TTL is not a built-in feature in Feature Store.
- ✓
Enable the online store
Why this is correct
Enabling the online store provisions a low-latency, high-availability store backed by ElastiCache or DynamoDB, which serves features at millisecond latency for real-time inference. This satisfies the stem's requirement for real-time recommendations, where offline-only storage would be too slow.
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