- A
AWS Data Pipeline with periodic S3 copy.
Why wrong: Not near real-time.
- B
Amazon Kinesis Data Streams with Kinesis Data Firehose delivery to S3.
Handles high throughput, Firehose batches to S3.
- C
Amazon MSK (Managed Streaming for Kafka) with Kafka Connect S3 sink.
Why wrong: More complex and costly.
- D
Amazon SQS FIFO queue with Lambda consumers writing to S3.
Why wrong: SQS FIFO throughput is limited (300 TPS).
Question 1,059 of 1,786
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data engineer is designing a streaming pipeline that ingests IoT sensor data from 10,000 devices. Each device sends a 1 KB message every second. The data must be processed in near real-time and stored in S3 for analytics. Which combination of services provides the most cost-effective solution?
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 Streams with Kinesis Data Firehose delivery to S3.
B is correct because Kinesis Data Streams ingests high-throughput IoT data (10,000 messages/sec at 1 KB each) with low latency, and Kinesis Data Firehose automatically batches and compresses data before delivering it to S3, eliminating the need for custom code or manual scaling. This combination provides the most cost-effective near-real-time solution by leveraging Firehose's built-in buffering and compression to minimize S3 storage costs and reduce the number of PUT requests.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 Data Pipeline with periodic S3 copy.
Why it's wrong here
Not near real-time.
- ✓
Amazon Kinesis Data Streams with Kinesis Data Firehose delivery to S3.
Why this is correct
Handles high throughput, Firehose batches to S3.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon MSK (Managed Streaming for Kafka) with Kafka Connect S3 sink.
Why it's wrong here
More complex and costly.
- ✗
Amazon SQS FIFO queue with Lambda consumers writing to S3.
Why it's wrong here
SQS FIFO throughput is limited (300 TPS).
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose MSK (Option C) thinking it is more scalable or flexible, but they overlook the higher operational cost and complexity for a simple S3 sink use case, where Kinesis Data Firehose's fully managed batching, compression, and direct S3 integration is more cost-effective and simpler to maintain.
Detailed technical explanation
How to think about this question
Kinesis Data Firehose uses a buffer interval (default 60 seconds) and buffer size (default 5 MB) to batch records before writing to S3, and it supports GZIP compression, which can reduce S3 storage costs by up to 80% for text-based IoT data. Under the hood, Kinesis Data Streams uses shards to scale throughput; with 10,000 1 KB messages per second, you would need approximately 10 shards (each shard supports 1 MB/s input and 1000 records/s), and Firehose can consume from the stream using a single delivery stream, automatically handling retries and error logging to S3 for failed records.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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 |
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Amazon Kinesis Data Streams with Kinesis Data Firehose delivery to S3. — B is correct because Kinesis Data Streams ingests high-throughput IoT data (10,000 messages/sec at 1 KB each) with low latency, and Kinesis Data Firehose automatically batches and compresses data before delivering it to S3, eliminating the need for custom code or manual scaling. This combination provides the most cost-effective near-real-time solution by leveraging Firehose's built-in buffering and compression to minimize S3 storage costs and reduce the number of PUT requests.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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