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Data Ingestion and Transformation →mediumMultiple ChoiceObjective-mapped

Quick Answer

The answer is Amazon Kinesis Data Streams, because it is a serverless streaming data service designed to ingest and process variable-volume, high-throughput data from thousands of IoT sources in real time. Its ability to handle unpredictable spikes without manual scaling makes it ideal for serverless real-time data ingestion for variable volume IoT use cases, as it automatically partitions and scales shards to match throughput demands. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your ability to distinguish between ingestion services: Kinesis Data Streams provides sub-second processing for real-time analytics, while Kinesis Data Firehose is a near-real-time delivery service to destinations like S3, and SQS is for decoupled messaging, not streaming. A common trap is choosing AWS IoT Core, which focuses on device connectivity and security rather than scalable streaming ingestion for analytics. Memory tip: think “Streams for streams”—if you need to process data as it arrives, Kinesis Data Streams is the serverless choice.

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 wants to ingest streaming data from thousands of IoT devices into AWS for real-time analytics. The data volume is variable and can spike unpredictably. The solution must be serverless and minimize operational overhead. Which AWS service should be used for ingestion?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

Question 1mediummultiple choice

Full question →

A
Use Amazon Kinesis Data Firehose to load streaming data directly into Amazon S3.
Why wrong: Amazon Kinesis Data Firehose is a service for loading streaming data into data stores, but it does not provide the same real-time processing capabilities as Kinesis Data Streams.
B
Use Amazon SQS to queue messages and process them in batches.
Why wrong: Amazon SQS is a message queuing service, not designed for real-time streaming analytics. It would add latency and not support the required real-time processing.
C
Use Amazon Kinesis Data Streams to ingest and process data in real time.
Amazon Kinesis Data Streams is a serverless streaming data service that can handle variable and high-throughput data from many sources, making it ideal for IoT data ingestion.
D
Use AWS IoT Core to ingest data and route it to Amazon DynamoDB.
Why wrong: AWS IoT Core is a managed cloud service that lets connected devices interact with cloud applications, but it is not primarily a streaming ingestion service for analytics.

Full breakdown with real-world context →

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

✓

Use Amazon Kinesis Data Streams to ingest and process data in real time.

Option B is correct because Amazon Kinesis Data Streams is a serverless streaming data service that can handle variable and high-throughput data from many sources, making it ideal for IoT data ingestion. Option A (Amazon SQS) is for message queuing, not real-time streaming analytics. Option C (Amazon Kinesis Data Firehose) is for loading streaming data into data stores, but it does not provide the same real-time processing capabilities as Kinesis Data Streams. Option D (AWS IoT Core) is a managed cloud service that lets connected devices easily and securely interact with cloud applications and other devices, but it is not primarily a streaming ingestion service for analytics.

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.

✗
Use Amazon Kinesis Data Firehose to load streaming data directly into Amazon S3.
Why it's wrong here
Amazon Kinesis Data Firehose is a service for loading streaming data into data stores, but it does not provide the same real-time processing capabilities as Kinesis Data Streams.
✗
Use Amazon SQS to queue messages and process them in batches.
Why it's wrong here
Amazon SQS is a message queuing service, not designed for real-time streaming analytics. It would add latency and not support the required real-time processing.
✓
Use Amazon Kinesis Data Streams to ingest and process data in real time.
Why this is correct
Amazon Kinesis Data Streams is a serverless streaming data service that can handle variable and high-throughput data from many sources, making it ideal for IoT data ingestion.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use AWS IoT Core to ingest data and route it to Amazon DynamoDB.
Why it's wrong here
AWS IoT Core is a managed cloud service that lets connected devices interact with cloud applications, but it is not primarily a streaming ingestion service for analytics.

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.

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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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: Use Amazon Kinesis Data Streams to ingest and process data in real time. — Option B is correct because Amazon Kinesis Data Streams is a serverless streaming data service that can handle variable and high-throughput data from many sources, making it ideal for IoT data ingestion. Option A (Amazon SQS) is for message queuing, not real-time streaming analytics. Option C (Amazon Kinesis Data Firehose) is for loading streaming data into data stores, but it does not provide the same real-time processing capabilities as Kinesis Data Streams. Option D (AWS IoT Core) is a managed cloud service that lets connected devices easily and securely interact with cloud applications and other devices, but it is not primarily a streaming ingestion service for analytics.

What should I do if I get this DEA-C01 question wrong?

Are there clue words in this question I should notice?

Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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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.