Quick Answer
The answer is Amazon Kinesis Data Analytics because the scenario explicitly requires applying transformations to streaming data in real time before landing it in Amazon S3. Kinesis Data Analytics, now part of Amazon Managed Service for Apache Flink, enables you to run SQL queries or Apache Flink applications directly against live data streams to perform filtering, aggregation, and enrichment, then output the transformed results to a destination like S3 via Kinesis Data Firehose. On the AWS Certified Solutions Architect Professional SAP-C02 exam, this question tests your ability to distinguish between raw ingestion services (Kinesis Data Streams) and transformation services; a common trap is choosing Kinesis Data Firehose alone, which can transform data but only with Lambda or simple format conversions, not the rich, stateful stream processing that Kinesis Data Analytics provides. Remember the key differentiator: if the requirement says “apply transformations” without specifying simple format changes, think Flink or SQL on the stream. A useful memory tip is “Analytics for active transforms, Firehose for passive delivery.”
This SAP-C02 practice question tests your understanding of design for new solutions. 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 designing a new application that will process streaming data from IoT devices. They need to ingest data in real time and apply transformations before storing it in Amazon S3. Which AWS service should they use?
Amazon Kinesis Data Firehose
Why wrong: Firehose loads data to destinations, but real-time transformations are limited.
Amazon SQS
Why wrong: SQS is a message queue, not a streaming analytics service.
Amazon Kinesis Data Analytics
Kinesis Data Analytics processes streaming data in real time.
AWS Lambda
Why wrong: Lambda can process data but is not purpose-built for streaming analytics.
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
Amazon Kinesis Data Analytics (now part of Amazon Managed Service for Apache Flink) is the correct choice because the question explicitly requires applying transformations to streaming data in real time before storing it in Amazon S3. Kinesis Data Analytics allows you to run SQL or Apache Flink applications directly on streaming data to perform transformations, aggregations, and filtering, and then output the results to a destination like Amazon S3 via Kinesis Data Firehose.
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.
Amazon Kinesis Data Firehose
Why it's wrong here
Firehose loads data to destinations, but real-time transformations are limited.
Amazon SQS
Why it's wrong here
SQS is a message queue, not a streaming analytics service.
Amazon Kinesis Data Analytics
Why this is correct
Kinesis Data Analytics processes streaming data in real time.
Related concept
Read the scenario before looking for a memorised answer.
AWS Lambda
Why it's wrong here
Lambda can process data but is not purpose-built for streaming analytics.
Common exam traps
The trap here is that candidates often confuse Kinesis Data Firehose's ability to deliver data to S3 with the need for real-time transformations, overlooking that Firehose only supports basic transformations and not the complex, stateful stream processing that Kinesis Data Analytics provides.
Detailed technical explanation
Under the hood, Kinesis Data Analytics uses Apache Flink to provide exactly-once processing semantics and support for event time, watermarking, and complex windowed aggregations. This enables use cases like real-time anomaly detection or sliding window averages on IoT sensor data, which cannot be achieved with simple Lambda-based transformations. The service can also read directly from Kinesis Data Streams or Amazon MSK, process the data using SQL or Flink, and then write to a Firehose delivery stream that lands the results in S3.
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
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FAQ
Design for New Solutions — This question tests Design for New Solutions — Read the scenario before looking for a memorised answer..
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 the question explicitly requires applying transformations to streaming data in real time before storing it in Amazon S3. Kinesis Data Analytics allows you to run SQL or Apache Flink applications directly on streaming data to perform transformations, aggregations, and filtering, and then output the results to a destination like Amazon S3 via Kinesis Data Firehose.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Same concept, more angles
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Variation 1. A company is designing a new application that will process streaming data from IoT devices. The data must be processed in real time and then stored in Amazon S3 for long-term analytics. Which combination of AWS services should be used?
easyWhy D: Option D is correct because Amazon Kinesis Data Streams ingests and buffers streaming IoT data in real time, AWS Lambda processes each record as it arrives, and the processed data is written directly to Amazon S3 for durable long-term analytics. This combination provides the low-latency, serverless pipeline required for real-time processing and S3-based storage.
Last reviewed: Jun 24, 2026
This SAP-C02 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 SAP-C02 exam.
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