DEA-C01 Data Ingestion and Transformation Practice Question
A data pipeline uses AWS Glue to read CSV files from an S3 bucket, transform them, and write Parquet back to S3. The pipeline runs daily and processes about 500 GB per run. The team wants to reduce costs without increasing runtime. Which approach is most effective?
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
✓
Optimize the Glue script to select only required columns and filter rows early.
Optimizing the Glue script to use column pruning and predicate pushdown reduces the amount of data scanned, lowering costs without increasing runtime. Option A (pre-converting CSV to Parquet) adds an extra processing step and cost, making it less effective. Option B (enabling job bookmarks) tracks already processed data but does not reduce the cost per run. Option C (increasing DPUs) may actually increase costs and can cause unpredictable runtime.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Pre-convert the CSV files to Parquet in S3 using a separate process.
Why it's wrong here
Pre-converting CSV to Parquet adds an extra processing step and cost, and does not reduce the cost of the main Glue job.
- ✗
Enable job bookmarks to skip already processed data.
Why it's wrong here
Job bookmarks track already processed data to avoid reprocessing, but for daily full runs of new data they do not reduce cost per run.
- ✗
Increase the number of DPUs for the Glue job to improve parallelism.
Why it's wrong here
Increasing DPUs improves parallelism but increases cost per hour, potentially raising overall cost and not reducing cost without increasing runtime.
- ✓
Optimize the Glue script to select only required columns and filter rows early.
Why this is correct
Selecting only required columns and filtering rows early reduces data scanned, lowering Glue job costs without increasing runtime.
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.