Question 1,648 of 1,711
DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is building a streaming pipeline using Amazon Kinesis Data Streams. The data must be enriched with reference data from a DynamoDB table before being written to S3. The engineer wants to minimize latency. Which architecture is BEST?
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 Kinesis Data Analytics for Apache Flink to enrich and output to Firehose.
(Kinesis Data Analytics for Apache Flink) is the best choice because it supports low-latency enrichment using external sources like DynamoDB via asynchronous I/O, meeting the requirement to minimize latency. Option A (AWS Glue streaming ETL) is designed for batch-oriented processing and introduces higher latency. Option C (Kinesis Data Firehose with a Lambda function) may experience cold starts and limited concurrency, increasing latency. Option D (Lambda polling the stream) also suffers from cold starts and scalability issues, making it less suitable for low-latency enrichment.
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 AWS Glue streaming ETL to read from Kinesis, enrich, and write to S3.
Why it's wrong here
Glue streaming ETL has higher latency than Flink.
- ✓
Use Kinesis Data Analytics for Apache Flink to enrich and output to Firehose.
Why this is correct
Flink provides low-latency streaming enrichment with external sources.
- ✗
Use Kinesis Data Firehose with a Lambda function for enrichment.
Why it's wrong here
Firehose's Lambda integration has higher latency due to invocation overhead.
- ✗
Use a Lambda function to poll the stream, enrich, and write to Firehose.
Why it's wrong here
Lambda polling can cause latency and scaling 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 |
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Last reviewed: Jun 20, 2026
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.
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