DEA-C01 Data Store Management Practice Question
A data engineering team is designing a data lake on Amazon S3. They need to store raw data in a format that supports schema evolution and is optimized for analytics with Amazon Athena. Which storage format should they use?
⚠ Common exam trap
Candidates often choose Avro or JSON because they are known for schema evolution, but they overlook that the question specifically asks for optimization with Amazon Athena, which requires a columnar format like Parquet to minimize scanned data and cost.
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
✓
Parquet
Parquet is the correct choice because it is a columnar storage format that is highly optimized for Amazon Athena, which can read only the necessary columns to minimize data scanned and reduce query costs. Parquet also supports schema evolution through features like nested data structures and the ability to add or remove columns without rewriting the entire dataset, making it ideal for raw data lakes that must accommodate changing schemas over time.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Parquet
Why this is correct
Parquet is columnar, supports schema evolution, and is optimized for Athena.
- ✗
CSV
Why it's wrong here
CSV lacks native schema evolution and is not columnar.
- ✗
Avro
Why it's wrong here
Avro is row-based and less efficient for analytical queries.
- ✗
JSON
Why it's wrong here
JSON is verbose and not columnar.
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.