MLS-C01 Data Engineering Practice Question
Which TWO AWS services can be used to transform data in transit before storing it in Amazon S3? (Choose TWO.)
⚠ Common exam trap
A common mix-up: candidates confuse query engines (like Athena or Redshift Spectrum) with transformation services, forgetting that in-transit transformation requires processing before the data reaches its final storage location.
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
✓
AWS Glue
AWS Glue is correct because it provides a serverless data integration service that can transform data in transit using its built-in transformation jobs (e.g., PySpark scripts) before writing the results to Amazon S3. This allows you to clean, enrich, or reshape streaming or batch data as it moves through the pipeline.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
AWS Glue
Why this is correct
Glue can process streaming data with streaming ETL jobs.
- ✗
Amazon Redshift Spectrum
Why it's wrong here
Redshift Spectrum queries data in S3, does not transform in transit.
- ✗
AWS Data Pipeline
Why it's wrong here
Data Pipeline moves data between sources, but not real-time transformation.
- ✓
Amazon Kinesis Data Firehose
Why this is correct
Firehose can transform data using Lambda before delivery.
- ✗
Amazon Athena
Why it's wrong here
Athena queries data at rest, not in transit.
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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