- A
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 wrong: Lambda is unnecessary; Kinesis Data Analytics can read directly from the stream.
- B
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 wrong: Lambda adds unnecessary cost and complexity.
- C
Use two Kinesis Data Streams: one for S3 delivery and one for Kinesis Data Analytics.
Why wrong: Two streams increase cost and management overhead.
- D
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.
Firehose can read from the stream and write to S3; Kinesis Data Analytics can read from the same stream for real-time analytics.
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 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?
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.
Option D is correct because 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.
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.
- ✗
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.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
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.
Detailed technical explanation
How to think about this question
Kinesis Data Streams uses shards to scale ingestion, with each shard supporting up to 1,000 records per second or 1 MB/s for writes. Kinesis Data Firehose can read from a stream via a Kinesis Data Streams source, automatically batching and delivering to S3 with optional conversion to Parquet or ORC. Kinesis Data Analytics uses an in-application stream to process data from the same stream in real time, enabling complex SQL-based analytics without additional data movement.
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
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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: 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. — Option D is correct because 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.
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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