DEA-C01 Data Ingestion and Transformation Practice Question
A company is using AWS Glue to run ETL jobs that transform data from Amazon DynamoDB to Amazon S3. The DynamoDB table has a large number of items (over 10 million) and is heavily used by production applications. The Glue job reads the entire DynamoDB table each time it runs, causing increased read capacity consumption and affecting production performance. The team wants to reduce the impact on the source DynamoDB table while still keeping the S3 data up-to-date. What should the team do?
⚠ Common exam trap
DEA-C01 often tests the misconception that increasing read capacity or reducing parallelism solves the impact on DynamoDB, but the real solution is to avoid full table scans by using change data capture with Streams and Lambda.
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
✓
Use DynamoDB Streams and AWS Lambda to capture changes and write them to S3, then run incremental Glue jobs.
Using DynamoDB Streams and AWS Lambda to capture changes and write them to S3, then running incremental Glue jobs, reduces the read load on the DynamoDB table because only changed data is processed. This approach keeps S3 data up-to-date without scanning the entire table, minimizing impact on production performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use DynamoDB Streams and AWS Lambda to capture changes and write them to S3, then run incremental Glue jobs.
Why this is correct
DynamoDB Streams capture item-level changes without consuming provisioned read capacity, so the production table is no longer scanned in full. Lambda writes those changes to S3, and Glue then processes only the incremental delta, satisfying the requirement to keep S3 current while removing the read-capacity impact on the heavily used source table.
- ✗
Increase the DynamoDB read capacity units to handle the Glue job's read load.
Why it's wrong here
Raising read capacity units absorbs the Glue scan but does not stop the job reading the entire table, so production traffic still competes for throughput and cost rises. It tempts teams treating capacity as the bottleneck, yet the fix is reading only changed items via DynamoDB Streams rather than provisioning more.
- ✗
Use the DynamoDB console to export the table to S3 in Parquet format.
Why it's wrong here
A full-table export still scans all 10 million items and produces a point-in-time snapshot, so it consumes the same read capacity and cannot keep S3 continuously current. It appeals as a native, serverless export, but it suits one-off migrations or archival, not recurring incremental replication.
- ✗
Reduce the parallelism of the Glue job to lower the read throughput.
Why it's wrong here
Lowering parallelism throttles the scan but still reads every item, so the full table is consumed each run and production read capacity remains affected. It tempts teams wanting a quick knob to turn, yet the requirement is incremental change capture, which DynamoDB Streams with Glue bookmarks provides.
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 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.