MLS-C01 Exploratory Data Analysis Practice Question
A data scientist is analyzing a dataset with 100 features and wants to identify which features are most correlated with the target variable. Which AWS service is most appropriate for this task?
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 SageMaker Data Wrangler
Amazon SageMaker Data Wrangler provides built-in data analysis and visualization capabilities, including correlation analysis, making it suitable for this task. Amazon QuickSight is a BI tool for dashboards, not for feature correlation analysis. Amazon Athena is a query service for data in S3, not for embedded data wrangling. AWS Glue DataBrew is a visual data preparation tool, but SageMaker Data Wrangler is more directly suited for correlation analysis.
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 QuickSight
Why it's wrong here
QuickSight is for visualization and dashboards, not embedded feature correlation analysis.
- ✗
Amazon Athena
Why it's wrong here
Athena is for querying data, not for correlation analysis.
- ✗
AWS Glue DataBrew
Why it's wrong here
DataBrew is for data preparation but lacks the integrated ML context of Data Wrangler.
- ✓
Amazon SageMaker Data Wrangler
Why this is correct
Data Wrangler provides data analysis and feature correlation within SageMaker Studio.
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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