DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is building a pipeline to ingest JSON files from Amazon S3 into Amazon Redshift. The files are 100 MB each and arrive every 5 minutes. Which service is BEST suited for this ingestion?
⚠ Common exam trap
The trap here is that candidates often overcomplicate the solution by choosing AWS Glue or Kinesis Firehose for batch ingestion, overlooking that the Redshift COPY command is the simplest, fastest, and most cost-effective option for bulk loading files from S3.
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
✓
Amazon Redshift COPY command
The Amazon Redshift COPY command is the most efficient and best-suited service for bulk loading 100 MB JSON files from S3 into Redshift at regular 5-minute intervals. It is optimized for high-throughput, parallel ingestion directly from S3, minimizing latency and resource overhead compared to other services.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS Glue ETL job
Why it's wrong here
AWS Glue ETL jobs are primarily designed for batch processing and complex data transformations. Starting a Spark cluster every 5 minutes for 100 MB files introduces significant overhead and latency, making it unsuitable for the frequent, low-latency ingestion required here, as its startup time would likely exceed the 5-minute window. Glue ETL is a strong choice for scenarios involving larger data volumes, less frequent ingestion schedules (e.g., hourly or daily), or when extensive data cleaning and transformation are necessary before loading into Redshift.
- ✓
Amazon Redshift COPY command
Why this is correct
COPY is optimized for loading large data from S3.
- ✗
AWS Lambda with Redshift Data API
Why it's wrong here
Lambda has time limits and is not efficient for large files.
- ✗
Amazon Kinesis Data Firehose with Redshift destination
Why it's wrong here
Firehose is for streaming data, not batch 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
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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.