- A
Amazon Kinesis Data Analytics
Kinesis Data Analytics can run SQL queries on streaming data from IoT Core in near real-time.
- B
AWS Glue
Why wrong: Glue is a batch ETL service, not designed for near real-time streaming.
- C
Amazon Redshift
Why wrong: Redshift is a data warehouse, not a real-time transformation service.
- D
Amazon Athena
Why wrong: Athena is for querying data in S3, not for real-time processing.
Question 486 of 1,786
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 data engineering team is ingesting streaming data from IoT devices using AWS IoT Core and needs to process the data in near real-time with minimal code. Which AWS service should they use to transform the data before storing it in Amazon S3?
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 Analytics
Amazon Kinesis Data Analytics (now part of Amazon Managed Service for Apache Flink) is the correct choice because it allows you to transform streaming data in near real-time using SQL or Apache Flink with minimal code. It can directly consume data from AWS IoT Core via Kinesis Data Streams or Amazon MSK, apply transformations like filtering, aggregation, or enrichment, and then output the processed data to Amazon S3 without requiring custom application servers.
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 Kinesis Data Analytics
Why this is correct
Kinesis Data Analytics can run SQL queries on streaming data from IoT Core in near real-time.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AWS Glue
Why it's wrong here
Glue is a batch ETL service, not designed for near real-time streaming.
- ✗
Amazon Redshift
Why it's wrong here
Redshift is a data warehouse, not a real-time transformation service.
- ✗
Amazon Athena
Why it's wrong here
Athena is for querying data in S3, not for real-time processing.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse AWS Glue's streaming ETL capability (which still requires writing Scala or Python code and managing checkpointing) with the 'minimal code' requirement, or they mistakenly think Amazon Athena can transform data before it lands in S3, when in fact Athena only queries data already stored.
Detailed technical explanation
How to think about this question
Under the hood, Kinesis Data Analytics for Apache Flink uses a runtime that continuously reads from a Kinesis data stream or MSK topic, applies user-defined Flink operators (e.g., map, filter, windowed aggregations), and writes results to a sink like S3 via the Flink S3 connector. A subtle behavior is that the service automatically manages checkpointing and state persistence in an internal Amazon S3 bucket, enabling exactly-once processing semantics for transformations. In a real-world scenario, an IoT device sending temperature readings can be filtered to only forward readings above a threshold, reducing storage costs and downstream processing load.
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 Analytics — Amazon Kinesis Data Analytics (now part of Amazon Managed Service for Apache Flink) is the correct choice because it allows you to transform streaming data in near real-time using SQL or Apache Flink with minimal code. It can directly consume data from AWS IoT Core via Kinesis Data Streams or Amazon MSK, apply transformations like filtering, aggregation, or enrichment, and then output the processed data to Amazon S3 without requiring custom application servers.
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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