Question 136 of 1,711
DEA-C01 Data Ingestion and Transformation Practice Question
A data engineering team needs to ingest streaming data from thousands of IoT devices. The data must be processed in near real-time and stored in Amazon S3 in Apache Parquet format partitioned by device_id and timestamp. Which combination of services should the team use to minimize operational overhead and cost?
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 Firehose, and optionally AWS Lambda.
Amazon Kinesis Data Streams ingests streaming data from thousands of IoT devices in near real-time. Kinesis Data Firehose delivers the data directly to Amazon S3 with built-in conversion to Apache Parquet and automatic partitioning by device_id and timestamp, minimizing operational overhead. AWS Lambda can optionally be used for lightweight transformations if needed. Option A is incorrect because using Amazon EC2 for processing adds significant operational overhead for scaling and management. Option B is incorrect because Amazon MSK (Kafka) and AWS Glue Streaming require more operational overhead and are not as cost-effective for this simple near-real-time use case. Option D is incorrect because S3 Transfer Acceleration is designed for large file transfers over long distances, not for streaming data ingestion, and AWS Lambda alone cannot handle continuous streaming without a dedicated ingestion service like Kinesis.
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, Amazon EC2 for processing, and Amazon S3 with lifecycle policies.
Why it's wrong here
EC2 adds operational overhead and is not serverless.
- ✗
Amazon MSK (Kafka), AWS Glue Streaming, and Amazon S3.
Why it's wrong here
MSK and Glue Streaming are valid but add more complexity compared to Kinesis Firehose.
- ✓
Amazon Kinesis Data Streams, Amazon Kinesis Data Firehose, and optionally AWS Lambda.
Why this is correct
Kinesis provides serverless ingestion and Firehose handles delivery, Parquet conversion, and partitioning.
- ✗
Amazon S3 Transfer Acceleration and AWS Lambda for event-driven transformation.
Why it's wrong here
S3 Transfer Acceleration is for large file uploads, not streaming.
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 |
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Last reviewed: Jun 20, 2026
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