easyMultiple Choice
MLA-C01 Practice Question: A data engineer needs to catalog metadata from…
A data engineer needs to catalog metadata from multiple data sources across the organization for use in ML workflows. Which AWS Glue component should be used to store and manage this metadata?
⚠ Common exam trap
MLA-C01 often tests the confusion between Glue Crawler (which populates the catalog) and Glue Data Catalog (which stores the metadata), causing candidates to select the crawler when the question asks where metadata is stored.
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 Data Catalog
The AWS Glue Data Catalog is a persistent, centralized metadata repository that stores table definitions, schemas, and partition information for data sources across the organization. It integrates natively with Athena, Redshift Spectrum, EMR, and Glue ETL jobs, making it the correct component for cataloging metadata used in ML workflows. Crawlers populate the Data Catalog, but the Catalog itself is the storage and management layer.
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 Crawler
Why it's wrong here
A Glue Crawler scans data sources and populates the Data Catalog with inferred schemas; it does not store or manage that metadata itself. It is tempting because crawlers are the usual way metadata enters the catalog, but the question asks which component holds it, so a crawler would be correct only if the stem asked how to discover and register new sources.
- ✗
AWS Glue Studio
Why it's wrong here
Glue Studio is a visual authoring interface for building and running ETL jobs; it does not itself store catalog metadata. It is tempting because Studio surfaces catalog tables while designing jobs, but the Data Catalog is the component that persists and manages metadata, so Studio would be correct only if the stem asked how to author transformation jobs graphically.
- ✓
AWS Glue Data Catalog
Why this is correct
The Glue Data Catalog is the central, Hive-compatible metastore that stores table definitions, schemas and partition metadata from crawlers across sources, giving ML workflows a single queryable catalogue. It satisfies the stem's requirement to store and manage metadata rather than transform or move data.
- ✗
AWS Glue ETL
Why it's wrong here
Glue ETL refers to the job engine that transforms and moves data using Spark or Python; it neither stores nor manages catalog metadata. It is tempting because ETL jobs read and write catalog tables, but the Data Catalog is the metadata repository, so Glue ETL would be correct only if the stem asked how to transform datasets.
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 and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.