DEA-C01 Data Ingestion and Transformation Practice Question
A data engineering team needs to ingest streaming data from an application into Amazon S3 for analytics. The data volume is moderate and the team wants the lowest operational overhead. Which AWS service should they use?
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 Kinesis Data Firehose
Amazon Kinesis Data Firehose is a fully managed service for loading streaming data into S3 with no code required and minimal operational overhead. Option A is incorrect because Amazon SQS is a message queue service, not designed for streaming data ingestion into S3. Option B is incorrect because AWS Glue is primarily a batch ETL service, not suitable for real-time streaming. Option C is incorrect because Amazon Kinesis Data Streams requires custom consumers and more management, increasing operational overhead.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon SQS
Why it's wrong here
Amazon SQS is a message queue that decouples producers from consumers; it does not deliver data into Amazon S3, so it cannot satisfy the ingestion target. It is tempting because SQS buffers streaming events reliably, and it would be correct as an intermediate buffer feeding a separate consumer that writes to S3.
- ✗
AWS Glue
Why it's wrong here
AWS Glue is a serverless ETL and data catalogue service for batch and transformation jobs, not a streaming ingestion pipeline into S3. It is tempting because Glue can read streams and write to S3, but that requires authoring and maintaining jobs, adding operational overhead the scenario explicitly wants minimised.
- ✗
Amazon Kinesis Data Streams
Why it's wrong here
Kinesis Data Streams requires provisioning and managing shards, capacity and consumers, adding operational overhead the team wants to avoid. It suits custom stream processing with sub-second latency and multiple consumers; for moderate-volume delivery into S3, Amazon Data Firehose handles scaling and delivery automatically.
- ✓
Amazon Kinesis Data Firehose
Why this is correct
Kinesis Data Firehose is fully managed, automatically scaling and delivering streaming data to Amazon S3 without managing clusters or consumers, meeting the lowest operational overhead constraint. Kinesis Data Streams would require provisioning shards and custom consumers, adding operational burden for moderate volume.
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 |
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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.