DEA-C01 Data Store Management Practice Question
A company uses Amazon Redshift for its data warehouse. The data engineering team loads data daily from Amazon S3 using COPY commands. Recently, the load performance has degraded because the S3 bucket contains many small files. The team needs to optimize the COPY operation to improve performance. Which approach should they take?
⚠ Common exam trap
Candidates often confuse scaling the cluster (Option B) with optimizing data ingestion, failing to recognize that the bottleneck is the number of S3 objects, not the cluster's compute capacity.
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 a manifest file that lists only the necessary files, and consolidate small files into larger ones before loading.
The performance degradation is caused by the overhead of processing many small files during the COPY command. Consolidating small files into larger ones (e.g., 100 MB–1 GB each) reduces the number of S3 GET requests and the metadata overhead on Redshift, directly improving load throughput. Using a manifest file further optimizes by explicitly listing only the required files, avoiding unnecessary S3 list operations.
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 Redshift Spectrum to query the data directly from S3 without loading.
Why it's wrong here
Spectrum is for querying, not loading.
- ✗
Increase the number of nodes in the Redshift cluster.
Why it's wrong here
Does not address the root cause of many small files.
- ✓
Use a manifest file that lists only the necessary files, and consolidate small files into larger ones before loading.
Why this is correct
Fewer large files improve COPY performance.
- ✗
Enable automatic compression on the Redshift table.
Why it's wrong here
Compression helps storage but not COPY performance from many small files.
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
Related to this question
About these practice questions
One of 1,711 original DEA-C01 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
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.