DEA-C01 Data Ingestion and Transformation Practice Question
A company uses AWS Glue to run ETL jobs that transform data from an Amazon S3 bucket (raw) to another S3 bucket (curated). The jobs run on a schedule and process data incrementally. The data engineer notices that the jobs are taking longer to complete each day, and the job metrics show that the number of DPUs (Data Processing Units) is underutilized. The engineer wants to improve job performance. What should the data engineer do?
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
✓
Increase the number of DPUs allocated to the Glue job to enable more parallelism.
Increasing the number of DPUs can improve parallelism and reduce job duration when the workload is parallelizable and DPUs are underutilized. Option B is wrong because AWS Glue Streaming is designed for real-time data, not scheduled batch processing, and would not address the performance issue. Option C is wrong because job bookmarks are already used for incremental processing and do not directly impact job speed. Option D is wrong because decreasing DPUs would reduce parallelism and likely increase job duration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Increase the number of DPUs allocated to the Glue job to enable more parallelism.
Why this is correct
Increasing DPUs can improve parallelism and reduce job duration if the workload is parallelizable and DPUs are underutilized.
- ✗
Switch from batch processing to streaming using AWS Glue Streaming.
Why it's wrong here
Switching to streaming is not suitable for scheduled batch jobs and would not improve performance; it is a different processing pattern.
- ✗
Enable job bookmarks to skip already processed data more efficiently.
Why it's wrong here
Job bookmarks are already used for incremental processing; they prevent reprocessing but do not directly affect job speed.
- ✗
Decrease the number of DPUs to reduce resource contention.
Why it's wrong here
Decreasing DPUs would reduce parallelism, likely increasing job duration, which is the opposite of the desired outcome.
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 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.