MLS-C01 Data Engineering Practice Question
A data scientist needs to perform exploratory data analysis on a 100 GB CSV file stored in Amazon S3. The data is not sensitive. The scientist wants to use SQL queries to filter and aggregate the data without setting up a server or moving the data. Which service should be used?
⚠ Common exam trap
AWS often tests the distinction between serverless query services (Athena) and services that require provisioning (EMR, Redshift), so the trap here is that candidates may choose Redshift Spectrum thinking it is serverless, but it actually requires an active Redshift cluster.
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 Athena
Amazon Athena is the correct choice because it is a serverless, interactive query service that allows you to run standard SQL directly on data stored in Amazon S3 without any infrastructure setup. For a 100 GB CSV file, Athena can handle the query workload efficiently by automatically scaling, and it charges only for the data scanned per query, making it ideal for ad-hoc exploratory analysis without moving or transforming the data.
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 it's wrong here
Glue is for ETL, not interactive querying.
- ✗
Amazon EMR
Why it's wrong here
EMR requires provisioning a cluster.
- ✓
Amazon Athena
Why this is correct
Athena is serverless and allows SQL queries on S3 data.
- ✗
Amazon Redshift Spectrum
Why it's wrong here
Redshift Spectrum requires a Redshift cluster to be running.
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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