DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is building a data pipeline that ingests data from Amazon S3 into Amazon Redshift. The data is in CSV format and includes a timestamp column. The pipeline should load only new data incrementally. Which approach is most efficient?
⚠ Common exam trap
A common mix-up: candidates think Redshift Spectrum is a valid alternative for loading data, but Spectrum is designed for external querying, not for persistent loading into Redshift tables, which is the explicit requirement in the question.
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 the COPY command with a manifest file that lists only the new S3 objects
Using the COPY command with a manifest file allows you to explicitly list only the new S3 objects to be loaded, enabling incremental loading without scanning or loading the entire bucket. This approach is efficient as it avoids the overhead of deduplication or full-bucket scans, and it leverages Redshift's native high-speed parallel ingestion from S3.
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 the COPY command to load the entire bucket and rely on Redshift to deduplicate
Why it's wrong here
COPY loads every object in the bucket each run; Redshift does not deduplicate rows automatically, so repeated loads duplicate data. It tempts because COPY is the standard bulk-load mechanism, but incremental ingestion requires tracking already-processed keys or using a manifest, not relying on implicit deduplication.
- ✓
Use the COPY command with a manifest file that lists only the new S3 objects
Why this is correct
A manifest listing only new S3 objects lets COPY load precisely those files, avoiding rescanning or reprocessing previously ingested data. This satisfies the incremental-load constraint efficiently, since Redshift reads just the specified object set rather than filtering the whole bucket.
- ✗
Use Amazon Redshift Spectrum to query the S3 data directly without loading
Why it's wrong here
Spectrum queries S3 externally, so it cannot apply the incremental load logic the pipeline needs; it suits ad-hoc analytics over S3 without ingesting. Redshift COPY with a manifest or timestamp filter loads only new rows into managed storage.
- ✗
Use INSERT statements within a loop to load each new file
Why it's wrong here
Row-by-row INSERTs bypass Redshift's parallel bulk-load architecture, so each file load is slow and inefficient. INSERT suits small targeted changes, not incremental ingestion of many CSV files, where COPY from S3 is the designed mechanism.
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.