DEA-C01 Data Ingestion and Transformation Practice Question
A data engineering team needs to transform CSV files stored in Amazon S3 into Parquet format using AWS Glue. The files are partitioned by date and are updated hourly. Which AWS Glue feature should be used to automatically detect the schema and partition structure?
⚠ Common exam trap
AWS often tests the distinction between tools that discover metadata (Crawler) versus tools that consume or transform data (Athena, DataBrew), leading candidates to pick Athena because it can query partitioned data, but it cannot automatically detect the partition structure without a pre-existing catalog.
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 Crawler
AWS Glue Crawler is the correct choice because it automatically scans data in S3, infers the schema (including data types), and detects the partition structure (e.g., date-based partitions like year/month/day) by examining the folder hierarchy. It then populates the AWS Glue Data Catalog with metadata, enabling ETL jobs to read the data without manual schema definition.
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 this is correct
Discovers schema and partitions automatically.
- ✗
AWS Glue DataBrew
Why it's wrong here
For visual data preparation, not schema discovery.
- ✗
AWS Lake Formation
Why it's wrong here
For data lake access control.
- ✗
Amazon Athena
Why it's wrong here
Query service, does not discover schema.
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 |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-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 DEA-C01 exam.