MLS-C01 Data Engineering Practice Question
A data scientist needs to process a large volume of streaming data from IoT devices and store the results in Amazon S3 for further analysis. Which AWS service is most suitable for ingesting and processing this data in near real-time?
⚠ Common exam trap
Watch out — candidates often confuse AWS Glue (batch ETL) with real-time processing, or assume Amazon Redshift can handle streaming ingestion via its COPY command, but neither supports true near real-time stream processing with sub-second latency.
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 Analytics
Amazon Kinesis Data Analytics is the most suitable service because it can process streaming data from IoT devices in near real-time using SQL or Apache Flink, and directly output the results to Amazon S3. It is designed for continuous, low-latency ingestion and analysis of data streams, making it ideal for this use case.
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 Redshift
Why it's wrong here
Redshift is a data warehouse, not for streaming ingestion.
- ✗
AWS Glue
Why it's wrong here
AWS Glue is a batch ETL service, not real-time.
- ✓
Amazon Kinesis Data Analytics
Why this is correct
Kinesis Data Analytics processes streaming data in real-time.
- ✗
Amazon EMR
Why it's wrong here
EMR is for big data processing, but not optimized for real-time 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 |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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