DEA-C01 Data Store Management Practice Question
A data engineer needs to create a table in Amazon Athena that reads JSON data stored in Amazon S3. The JSON records are stored in a single file, one JSON object per line. The engineer wants Athena to automatically discover the schema and create the table without manually defining columns. Which AWS service or feature should the engineer use?
⚠ Common exam trap
The trap here is assuming that Athena can automatically infer schemas from raw data without a crawler or manual DDL.
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
An AWS Glue crawler automatically scans data in Amazon S3, infers the schema, and creates table definitions in the AWS Glue Data Catalog. Athena uses this catalog to query the data without manual schema definition. This is the standard method for automatic schema discovery in a data lake.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon Athena CREATE TABLE AS SELECT (CTAS) statement
Why it's wrong here
CTAS creates a new table from the results of a SELECT query, but it requires an existing table to query. It does not discover schemas from raw data. It is used for data transformation and storage, not for initial schema inference.
- ✓
AWS Glue crawler
Why this is correct
AWS Glue crawler scans data in S3, infers the schema, and populates the AWS Glue Data Catalog. Athena can then query the table using the catalog metadata. This meets the requirement of automatic schema discovery without manual column definition.
- ✗
AWS Glue DataBrew
Why it's wrong here
DataBrew is a visual data preparation tool for cleaning and transforming data. It does not automatically create tables in the Glue Data Catalog for Athena. It is used for profiling and cleaning, not for schema discovery and cataloging.
- ✗
Amazon S3 Inventory
Why it's wrong here
S3 Inventory provides a scheduled report of objects and metadata in a bucket, but it does not infer schemas or create tables in the Glue Data Catalog. It is used for auditing and inventory management, not for querying data with Athena.
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
Related to this question
About these practice questions
Courseiva writes every DEA-C01 question from scratch — 1,321 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
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 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.