- A
Amazon EMR with Spark Streaming
Why wrong: Amazon EMR with Spark Streaming is optimized for large-scale batch and stream processing but is not the simplest or most direct service for this specific use case. Spark Streaming typically uses Scala or Java, and while PySpark can be used, it adds complexity compared to using Kinesis Data Analytics for Apache Flink with the Python API.
- B
AWS Lambda function triggered by Kinesis Data Streams
Why wrong: AWS Lambda can be triggered by Kinesis Data Streams for real-time processing, but it has limitations such as a maximum execution time of 15 minutes and is better suited for lightweight, simple transformations rather than complex custom Python code.
- C
Kinesis Data Analytics for Apache Flink
Kinesis Data Analytics for Apache Flink is the correct choice because it allows running custom Apache Flink applications that support custom Python code via the Apache Flink Python API, enabling real-time data transformation.
- D
Kinesis Data Firehose with custom data transformation
Why wrong: Kinesis Data Firehose can perform data transformation using Lambda functions, but it does not support arbitrary custom Python code directly. It is primarily designed for loading streaming data into destinations like S3 with built-in or Lambda-based transformations.
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.
A company is ingesting streaming data from IoT devices into Amazon Kinesis Data Streams. The data must be transformed in real-time using custom Python code before being stored in Amazon S3. Which AWS service should be used to perform this transformation?
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
Kinesis Data Analytics for Apache Flink
Option A is Amazon EMR with Spark Streaming, which is optimized for large-scale batch and stream processing but is not the simplest or most direct service for this specific use case. Option B is AWS Lambda, which can be used for simple transformations but has limitations on execution time and complexity. Option D is Kinesis Data Firehose with custom data transformation, which supports only built-in transformations or Lambda functions, not arbitrary custom Python code directly. Option C, Kinesis Data Analytics for Apache Flink, is correct because it allows running custom Apache Flink applications, which support custom Python code via the Apache Flink Python API, for real-time data 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.
- ✗
Amazon EMR with Spark Streaming
Why it's wrong here
Amazon EMR with Spark Streaming is optimized for large-scale batch and stream processing but is not the simplest or most direct service for this specific use case. Spark Streaming typically uses Scala or Java, and while PySpark can be used, it adds complexity compared to using Kinesis Data Analytics for Apache Flink with the Python API.
- ✗
AWS Lambda function triggered by Kinesis Data Streams
Why it's wrong here
AWS Lambda can be triggered by Kinesis Data Streams for real-time processing, but it has limitations such as a maximum execution time of 15 minutes and is better suited for lightweight, simple transformations rather than complex custom Python code.
- ✓
Kinesis Data Analytics for Apache Flink
Why this is correct
Kinesis Data Analytics for Apache Flink is the correct choice because it allows running custom Apache Flink applications that support custom Python code via the Apache Flink Python API, enabling real-time data transformation.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Kinesis Data Firehose with custom data transformation
Why it's wrong here
Kinesis Data Firehose can perform data transformation using Lambda functions, but it does not support arbitrary custom Python code directly. It is primarily designed for loading streaming data into destinations like S3 with built-in or Lambda-based transformations.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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Data Ingestion and Transformation — study guide chapter
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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: Kinesis Data Analytics for Apache Flink — Option A is Amazon EMR with Spark Streaming, which is optimized for large-scale batch and stream processing but is not the simplest or most direct service for this specific use case. Option B is AWS Lambda, which can be used for simple transformations but has limitations on execution time and complexity. Option D is Kinesis Data Firehose with custom data transformation, which supports only built-in transformations or Lambda functions, not arbitrary custom Python code directly. Option C, Kinesis Data Analytics for Apache Flink, is correct because it allows running custom Apache Flink applications, which support custom Python code via the Apache Flink Python API, for real-time data transformation.
What should I do if I get this DEA-C01 question wrong?
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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: Jun 20, 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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