DEA-C01 Data Operations and Support Practice Question
A data engineer is designing a data pipeline that ingests data from multiple sources into Amazon S3, then processes it with AWS Glue and loads it into Amazon Redshift. Which THREE practices should be implemented to ensure data quality?
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
✓
Implement data validation checks at the ingestion stage
Implementing data validation checks at the ingestion stage ensures that only valid data enters the pipeline, catching issues early. Option B is correct because AWS Glue DataBrew provides data profiling and schema enforcement capabilities that help maintain data quality by identifying anomalies and enforcing schemas. Option E is correct because setting up Amazon CloudWatch alarms allows proactive monitoring of pipeline failures and data anomalies, enabling timely responses. Option C is incorrect because compressing data files reduces storage costs but does not directly address data quality. Option D is incorrect because manual sampling is not scalable and cannot consistently ensure data quality in large-scale pipelines.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Implement data validation checks at the ingestion stage
Why this is correct
Early validation catches errors before processing.
- ✓
Use AWS Glue DataBrew for data profiling and schema enforcement
Why this is correct
DataBrew helps profile data and enforce schemas.
- ✗
Compress data files to reduce storage costs
Why it's wrong here
Compression does not affect data quality.
- ✗
Use manual sampling to check data quality periodically
Why it's wrong here
Manual sampling is not automated and may miss issues.
- ✓
Set up Amazon CloudWatch alarms for pipeline failures and data anomalies
Why this is correct
Monitoring allows rapid response to quality issues.
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.