- A
Use Amazon S3 Transfer Acceleration with S3 Event Notifications to trigger AWS Lambda for processing.
Why wrong: S3 Transfer Acceleration accelerates uploads to S3 but is not designed for streaming ingestion; S3 Event Notifications have latency and are not ideal for near-real-time.
- B
Use Amazon Kinesis Data Firehose to ingest data into Amazon S3 and use AWS Lambda to transform data during delivery.
Why wrong: Kinesis Data Firehose buffers data before delivering to S3, which introduces latency and is not suitable for sub-second analytics.
- C
Use Amazon Simple Queue Service (SQS) to buffer the streaming data and configure an Auto Scaling group of EC2 instances to poll and process the data.
Why wrong: SQS is a message queue, not a streaming platform; it does not support partitioning, replay, or ordered processing across shards.
- D
Use Amazon Kinesis Data Streams to ingest the data and AWS Lambda to process records in real-time with automatic scaling.
Kinesis Data Streams provides durable, scalable, low-latency ingestion; Lambda can process each shard in parallel and scales automatically.
Quick Answer
The answer is to use Amazon Kinesis Data Streams for ingestion and AWS Lambda for processing. This combination is correct because Kinesis Data Streams provides durable, scalable storage for streaming data as soon as it arrives, handling unpredictable spikes from thousands of IoT devices without provisioning overhead, while Lambda automatically scales to process records in near-real-time, ensuring sub-second latency without managing servers. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of real-time stream processing versus batch-oriented services; a common trap is choosing Kinesis Data Firehose, which introduces buffering delays and lacks the sub-second latency required for true real-time analytics. Remember the memory tip: “Kinesis for the stream, Lambda for the dream”—Kinesis holds the data durably, and Lambda processes it instantly, unlike Firehose’s batch delivery or SQS’s lack of partitioning and replay.
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 engineer needs to ingest streaming data from thousands of IoT devices into AWS for near-real-time analytics. The data volume varies significantly and can spike unpredictably. The engineer wants to minimize operational overhead and ensure that data is durably stored as soon as it arrives. Which AWS service combination should the engineer use?
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.
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 the data and AWS Lambda to process records in real-time with automatic scaling.
Option D is correct because Kinesis Data Streams provides durable, scalable ingestion for streaming data, and Lambda can process records in near-real-time with automatic scaling. Option A is wrong because S3 Transfer Acceleration is for accelerating uploads to S3, not for streaming ingestion. Option B is wrong because Kinesis Data Firehose is designed for loading streaming data into destinations like S3 but does not offer sub-second latency and has buffering delays. Option C is wrong because SQS is a message queue that decouples producers and consumers but does not natively support streaming data partitioning or replay.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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 S3 Transfer Acceleration with S3 Event Notifications to trigger AWS Lambda for processing.
Why it's wrong here
S3 Transfer Acceleration accelerates uploads to S3 but is not designed for streaming ingestion; S3 Event Notifications have latency and are not ideal for near-real-time.
- ✗
Use Amazon Kinesis Data Firehose to ingest data into Amazon S3 and use AWS Lambda to transform data during delivery.
Why it's wrong here
Kinesis Data Firehose buffers data before delivering to S3, which introduces latency and is not suitable for sub-second analytics.
- ✗
Use Amazon Simple Queue Service (SQS) to buffer the streaming data and configure an Auto Scaling group of EC2 instances to poll and process the data.
Why it's wrong here
SQS is a message queue, not a streaming platform; it does not support partitioning, replay, or ordered processing across shards.
- ✓
Use Amazon Kinesis Data Streams to ingest the data and AWS Lambda to process records in real-time with automatic scaling.
Why this is correct
Kinesis Data Streams provides durable, scalable, low-latency ingestion; Lambda can process each shard in parallel and scales automatically.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.
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Data Ingestion and Transformation — study guide chapter
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Data Ingestion and Transformation practice questions
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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 — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Use Amazon Kinesis Data Streams to ingest the data and AWS Lambda to process records in real-time with automatic scaling. — Option D is correct because Kinesis Data Streams provides durable, scalable ingestion for streaming data, and Lambda can process records in near-real-time with automatic scaling. Option A is wrong because S3 Transfer Acceleration is for accelerating uploads to S3, not for streaming ingestion. Option B is wrong because Kinesis Data Firehose is designed for loading streaming data into destinations like S3 but does not offer sub-second latency and has buffering delays. Option C is wrong because SQS is a message queue that decouples producers and consumers but does not natively support streaming data partitioning or replay.
What should I do if I get this DEA-C01 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.
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?
Static NAT maps one inside address to one outside address.
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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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