- A
Ability to deliver data directly to Amazon Redshift [wrong]
Firehose can deliver to Redshift; KDS requires additional services.
- B
Data retention period longer than 7 days [CORRECT]
Correct. Kinesis Data Streams supports a data retention period from 24 hours up to 365 days, while Kinesis Data Firehose does not retain data (it delivers data immediately). This is a key consideration when choosing between the two services.
- C
Automatic scaling of ingestion throughput [CORRECT]
Why wrong: Firehose auto-scales; KDS requires manual shard management.
- D
Lower cost per GB ingested [wrong]
Why wrong: Cost depends on usage; KDS can be cheaper for low volumes.
- E
Need for custom data processing using AWS Lambda or KCL [CORRECT]
KDS supports custom consumers; Firehose does not.
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
Which THREE factors should be considered when choosing between Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose for a streaming ingestion architecture? (Choose 3.)
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
Ability to deliver data directly to Amazon Redshift [wrong]
Amazon Kinesis Data Firehose can deliver data directly to Amazon Redshift via an intermediate Amazon S3 bucket, making option A a factor to consider. Option C is a factor because Kinesis Data Firehose automatically scales its throughput, while Kinesis Data Streams requires manual shard management. Option E is a factor because Kinesis Data Streams supports custom data processing using the Kinesis Client Library (KCL) or AWS Lambda, whereas Firehose only supports Lambda for transformation.
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.
- ✓
Ability to deliver data directly to Amazon Redshift [wrong]
Why this is correct
Firehose can deliver to Redshift; KDS requires additional services.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Data retention period longer than 7 days [CORRECT]
Why this is correct
Correct. Kinesis Data Streams supports a data retention period from 24 hours up to 365 days, while Kinesis Data Firehose does not retain data (it delivers data immediately). This is a key consideration when choosing between the two services.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Automatic scaling of ingestion throughput [CORRECT]
Why it's wrong here
Firehose auto-scales; KDS requires manual shard management.
- ✗
Lower cost per GB ingested [wrong]
Why it's wrong here
Cost depends on usage; KDS can be cheaper for low volumes.
- ✓
Need for custom data processing using AWS Lambda or KCL [CORRECT]
Why this is correct
KDS supports custom consumers; Firehose does not.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The DEA-C01 exam often tests the misconception that all listed features are equally important when choosing between the two services. The trap here is that direct Redshift delivery (option A) is often considered a differentiator, but it is not a primary factor because both services can achieve it with additional steps. Candidates may incorrectly select all four seemingly correct options, but only three are key factors.
Detailed technical explanation
How to think about this question
Kinesis Data Streams uses shards to scale ingestion throughput, and each shard provides 1 MB/s input and 2 MB/s output; scaling requires manual or API-based shard splitting. Kinesis Data Firehose automatically scales to handle throughput without manual intervention, making option C correct. Option E is correct because Kinesis Data Streams natively supports custom processing via AWS Lambda (using the Kinesis trigger) or the Kinesis Client Library (KCL), while Firehose only supports Lambda for transformation, not full custom consumer 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 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.
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: Ability to deliver data directly to Amazon Redshift [wrong] — Amazon Kinesis Data Firehose can deliver data directly to Amazon Redshift via an intermediate Amazon S3 bucket, making option A a factor to consider. Option C is a factor because Kinesis Data Firehose automatically scales its throughput, while Kinesis Data Streams requires manual shard management. Option E is a factor because Kinesis Data Streams supports custom data processing using the Kinesis Client Library (KCL) or AWS Lambda, whereas Firehose only supports Lambda for transformation.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 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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