DEA-C01 Data Operations and Support Practice Question
A data engineer is designing a data lake on Amazon S3. The data is ingested from multiple sources and must be queryable using Amazon Athena. The engineer needs to optimize query performance and reduce costs. Which THREE actions would achieve this?
⚠ Common exam trap
It's easy for candidates to confuse 'more files = more parallelism' with Athena's actual recommendation of fewer, larger files to minimize the overhead of S3 list and get operations, and they may also mistake S3 Select as a viable alternative to Athena for full SQL querying.
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
✓
Partition the data by a commonly used filter column.
Partitioning data by a commonly used filter column (e.g., date, region) allows Athena to prune partitions during query execution, scanning only the relevant S3 prefixes. This reduces the amount of data read per query, directly lowering both query latency and cost, as Athena charges based on the volume of data scanned.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Store data in many small files to increase parallelism.
Why it's wrong here
Many small files increase overhead and Athena charges per query.
- ✓
Partition the data by a commonly used filter column.
Why this is correct
Partition pruning limits the data scanned.
- ✗
Use S3 Select instead of Athena for queries.
Why it's wrong here
S3 Select is not a replacement for Athena; it's a different service.
- ✓
Compress data with a splittable compression format like Snappy.
Why this is correct
Compression reduces storage and I/O.
- ✓
Convert data to Apache Parquet or ORC format.
Why this is correct
Columnar formats reduce data scanned.
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.