Quick Answer
The answer is Amazon Kinesis Data Analytics for Apache Flink, as it is purpose-built for the real-time transformation of Kinesis data streams using Apache Flink’s powerful, stateful stream processing engine. This service allows you to define complex, continuous transformations—such as aggregations, filtering, and joins—directly on the incoming data before it lands in Amazon S3, making it the ideal choice for high-throughput IoT workloads. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your ability to distinguish between real-time and near-real-time or batch services; a common trap is selecting AWS Lambda, which works well for lightweight, stateless transformations but lacks the native support for stateful operations and checkpointing that Flink provides. Remember the memory tip: “Flink for Flowing, Lambda for Lightweight”—if the transformation requires maintaining state across events or complex windowed logic, think Flink.
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 streaming IoT data from thousands of devices into Amazon Kinesis Data Streams. The data must be transformed in real time before being stored in Amazon S3. Which service should be used to perform the transformation as the data streams through Kinesis?
AWS Glue
Why wrong: Glue is primarily for batch ETL, not real-time streaming.
Amazon Kinesis Data Analytics for Apache Flink
Correctly processes streaming data in real time with Flink.
Amazon EMR
Why wrong: EMR can process streaming data but adds operational overhead and latency.
AWS Lambda
Why wrong: Lambda can process records from Kinesis but is stateless and limited in duration.
Answer choices
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 Analytics for Apache Flink
Option A is correct because Amazon Kinesis Data Analytics for Apache Flink can process streaming data in real time using Flink, which is ideal for transformations. Option B (Lambda) can process records but is better for lightweight transformations and may not handle complex stateful operations. Option C (Glue) is batch-oriented, not real-time. Option D (EMR) is for big data processing but adds latency.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
AWS Glue
Why it's wrong here
Glue is primarily for batch ETL, not real-time streaming.
Amazon Kinesis Data Analytics for Apache Flink
Why this is correct
Correctly processes streaming data in real time with Flink.
Related concept
Read the scenario before looking for a memorised answer.
Amazon EMR
Why it's wrong here
EMR can process streaming data but adds operational overhead and latency.
AWS Lambda
Why it's wrong here
Lambda can process records from Kinesis but is stateless and limited in duration.
Common exam traps
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
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.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
What to study next
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.
Data Ingestion and Transformation — study guide chapter
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FAQ
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
The correct answer is: Amazon Kinesis Data Analytics for Apache Flink — Option A is correct because Amazon Kinesis Data Analytics for Apache Flink can process streaming data in real time using Flink, which is ideal for transformations. Option B (Lambda) can process records but is better for lightweight transformations and may not handle complex stateful operations. Option C (Glue) is batch-oriented, not real-time. Option D (EMR) is for big data processing but adds latency.
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.
Read the scenario before looking for a memorised answer.
About these practice questions
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Same concept, more angles
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company is ingesting streaming data from IoT devices into Amazon Kinesis Data Streams. The data must be transformed in real-time and then stored in Amazon S3. Which AWS service should be used to perform the transformation?
easyWhy C: Option A is correct because Amazon Kinesis Data Analytics can process and transform streaming data in real-time using SQL or Apache Flink. Option B is wrong because AWS Glue is a batch ETL service, not real-time. Option C is wrong because Amazon EMR is for big data processing, not real-time streaming transformation. Option D is wrong because Amazon Athena is an interactive query service, not for real-time transformation.
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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