DEA-C01 Data Ingestion and Transformation Practice Question
A company needs to ingest streaming data from thousands of IoT devices. The data must be processed in real-time and stored in Amazon S3. Which TWO services should be used together?
⚠ Common exam trap
Test-takers frequently confuse Kinesis Data Firehose with Kinesis Data Streams, thinking only one is needed, but the question requires both: Data Streams for real-time ingestion from devices and Data Firehose for automated delivery to 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 Streams
Amazon Kinesis Data Streams (A) is correct because it provides a highly scalable, real-time streaming ingestion layer that can continuously capture data from thousands of IoT devices with low latency and durable, ordered record storage across shards. Amazon Kinesis Data Firehose (B) is correct because it is the fully managed delivery service that can consume that streaming data and automatically batch, transform, and load it directly into Amazon S3 without writing custom consumer applications. Together they satisfy the requirement for real-time processing plus reliable storage in S3. AWS Glue (C) is a serverless ETL and data catalog service, not a streaming ingestion or delivery mechanism, so it does not fit this pipeline. Amazon SQS (D) is a message queue for decoupling applications, not a real-time streaming service designed for high-throughput IoT telemetry or direct S3 delivery. AWS Direct Connect (E) is a dedicated network connection from on-premises to AWS, not a data streaming or processing service.
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 Streams
Why this is correct
Kinesis Data Streams ingests the high-volume IoT telemetry with low latency and durable, replicated storage, buffering thousands of device writes for downstream consumers. It satisfies the real-time processing requirement by feeding analytics or Lambda consumers before data lands in S3.
- ✓
Amazon Kinesis Data Firehose
Why this is correct
Kinesis Data Firehose batches and delivers the stream directly into Amazon S3 with configurable buffering, compression and format conversion, requiring no consumer code. It satisfies the storage requirement by handling the durable S3 delivery leg of the pipeline.
- ✗
AWS Glue
Why it's wrong here
AWS Glue is a batch-oriented ETL service driven by crawlers and jobs; it cannot ingest continuous IoT streams or process them in real time. It is tempting because Glue catalogues and transforms data destined for Amazon S3, and it would be correct for scheduled batch ETL over data already landed in S3.
- ✗
Amazon Simple Queue Service (SQS)
Why it's wrong here
SQS is a message queue, not a stream processor; it cannot ingest thousands of IoT device streams or write processed output to Amazon S3 in real time. It is tempting because SQS decouples producers from consumers, and it would be the right choice for buffering discrete messages between application tiers.
- ✗
AWS Direct Connect
Why it's wrong here
Direct Connect is a dedicated private network link between on-premises infrastructure and AWS, not a streaming ingestion or processing service. It suits hybrid connectivity with predictable bandwidth; IoT ingestion requires Kinesis Data Streams and Firehose instead.
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 |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.