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MLA-C01 Practice Question: A financial services company ingests transaction…
A financial services company ingests transaction data from multiple sources into an S3 data lake. They want to use AWS Glue to catalog this data and make it queryable by Amazon Athena. The data schema changes frequently as new sources are added. Which AWS Glue feature should they enable to automatically detect and update the schema?
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
✓
AWS Glue crawlers with schema update policy set to 'UPDATE'
AWS Glue crawlers can automatically scan data in S3, infer schemas, and update the Data Catalog. Schema evolution is supported natively when crawlers are configured to update table definitions. Manual schema definition would not handle frequent changes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS Glue DataBrew
Why it's wrong here
DataBrew is a visual data preparation tool, not for automated schema discovery.
- ✓
AWS Glue crawlers with schema update policy set to 'UPDATE'
Why this is correct
Crawlers automatically detect new partitions and schema changes, updating the Data Catalog accordingly.
- ✗
AWS Glue ETL job scheduled to run daily
Why it's wrong here
ETL jobs transform data but do not automatically catalog schema changes.
- ✗
Manual schema definition in the AWS Glue Data Catalog
Why it's wrong here
Manual definition is not scalable for frequent schema changes.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLA-C01 exam.