- A
Amazon EC2 with Apache Kafka -> S3
Why wrong: Requires managing EC2; not serverless.
- B
Amazon Kinesis Data Streams -> AWS Lambda for dashboard -> Amazon Kinesis Data Firehose -> S3
Streams provide buffer, Firehose delivers to S3, Lambda processes for dashboard.
- C
Amazon Kinesis Data Firehose directly with no buffer
Why wrong: Firehose can lose data if throttled without a stream.
- D
Amazon SQS -> AWS Lambda -> S3
Why wrong: SQS is not designed for high-throughput streaming.
Question 758 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 company is ingesting streaming data from a fleet of weather sensors. Each sensor sends a JSON payload every second. The data is used for real-time dashboarding and also archived to S3. The pipeline should handle sudden bursts of data without data loss. Which architecture meets these requirements?
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 -> AWS Lambda for dashboard -> Amazon Kinesis Data Firehose -> S3
Option B is correct because Kinesis Data Streams provides durable, scalable ingestion that can handle sudden bursts of data without loss, while Lambda processes records for real-time dashboarding and Kinesis Data Firehose reliably buffers and archives data to S3. This decoupled architecture ensures no data is lost even during traffic spikes, as Kinesis Data Streams retains data for up to 365 days and Firehose can buffer incoming records before writing to S3.
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.
- ✗
Amazon EC2 with Apache Kafka -> S3
Why it's wrong here
Requires managing EC2; not serverless.
- ✓
Amazon Kinesis Data Streams -> AWS Lambda for dashboard -> Amazon Kinesis Data Firehose -> S3
Why this is correct
Streams provide buffer, Firehose delivers to S3, Lambda processes for dashboard.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon Kinesis Data Firehose directly with no buffer
Why it's wrong here
Firehose can lose data if throttled without a stream.
- ✗
Amazon SQS -> AWS Lambda -> S3
Why it's wrong here
SQS is not designed for high-throughput streaming.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The DEA-C01 exam often tests the misconception that Kinesis Data Firehose can be used as a standalone ingestion service without a buffer, but the trap here is that Firehose requires a buffer (minimum 60 seconds or 1 MB) to function, and without it, data would be lost during bursts, making Option C an incorrect choice.
Detailed technical explanation
How to think about this question
Kinesis Data Streams uses shards to scale ingestion, each supporting up to 1 MB/s or 1,000 records/s for writes, and you can auto-scale shards using the UpdateShardCount API or on-demand mode to handle bursts. Kinesis Data Firehose buffers data based on a configurable buffer size (1–128 MB) or buffer interval (60–900 seconds), ensuring that even if Lambda processing lags, data is safely delivered to S3 with no loss. In real-world scenarios, weather sensor fleets can generate millions of records per second during storms, and this architecture allows Lambda to filter or aggregate data for dashboards while Firehose handles bulk archiving, avoiding the need for custom checkpointing or retry logic.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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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 -> AWS Lambda for dashboard -> Amazon Kinesis Data Firehose -> S3 — Option B is correct because Kinesis Data Streams provides durable, scalable ingestion that can handle sudden bursts of data without loss, while Lambda processes records for real-time dashboarding and Kinesis Data Firehose reliably buffers and archives data to S3. This decoupled architecture ensures no data is lost even during traffic spikes, as Kinesis Data Streams retains data for up to 365 days and Firehose can buffer incoming records before writing to S3.
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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