DEA-C01 Data Ingestion and Transformation Practice Question
A company is ingesting streaming data from social media feeds using Amazon Kinesis Data Streams. The data volume peaks at 10,000 records per second, and each record is up to 1 KB. The company needs to archive the raw data in Amazon S3 in near real-time and also make it available for real-time analytics using Amazon Kinesis Data Analytics. What is the MOST efficient architecture to meet these requirements?
⚠ Common exam trap
The trap here is that candidates often overcomplicate the architecture by adding unnecessary Lambda functions or duplicate streams, not realizing that Kinesis Data Firehose and Kinesis Data Analytics can both consume from the same Kinesis Data Stream natively.
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 Streams as the ingestion point. Use Kinesis Data Firehose to read from the stream and write to S3. Use Kinesis Data Analytics to read directly from the same stream.
Kinesis Data Streams can serve as a single ingestion point, with Kinesis Data Firehose reading from the stream to deliver data to S3 (with optional transformation) and Kinesis Data Analytics reading directly from the same stream for real-time analytics. This avoids unnecessary duplication of streams or Lambda-based processing, which would add latency and complexity. The architecture is the most efficient as it leverages native integrations without intermediate compute.
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 Kinesis Data Streams as the ingestion point. Use Kinesis Data Firehose to read from the stream, convert to Parquet, and write to S3. Use a Lambda function to send data to Kinesis Data Analytics.
Why it's wrong here
Lambda is unnecessary; Kinesis Data Analytics can read directly from the stream.
- ✗
Use Kinesis Data Streams as the ingestion point. Use a Lambda function to read from the stream, write to S3, and send data to Kinesis Data Analytics.
Why it's wrong here
Lambda adds unnecessary cost and complexity.
- ✗
Use two Kinesis Data Streams: one for S3 delivery and one for Kinesis Data Analytics.
Why it's wrong here
Two streams increase cost and management overhead.
- ✓
Use Kinesis Data Streams as the ingestion point. Use Kinesis Data Firehose to read from the stream and write to S3. Use Kinesis Data Analytics to read directly from the same stream.
Why this is correct
Firehose can read from the stream and write to S3; Kinesis Data Analytics can read from the same stream for real-time analytics.
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.