Question 162 of 1,672
MLS-C01 Exploratory Data Analysis Practice Question
A data scientist is using Amazon SageMaker Studio notebooks for EDA. They want to share a reproducible report that includes code, visualizations, and narrative text with their team. Which approach should they use?
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
✓
Save the notebook as an .ipynb file and share it via Amazon S3.
A Jupyter notebook (.ipynb) saved in SageMaker Studio contains code, visualizations, and narrative text, and sharing it via Amazon S3 allows team members to reproduce and interact with the analysis. Option B (SageMaker Clarify) is for bias detection and model explainability, not for sharing EDA reports. Option C (Amazon QuickSight) is used for interactive dashboards and does not include the underlying code. Option D (SageMaker Autopilot) automates model building and does not generate a shareable EDA report.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Save the notebook as an .ipynb file and share it via Amazon S3.
Why this is correct
Correct. A .ipynb file preserves code, output, and markdown, making it fully reproducible when shared via S3.
- ✗
Use Amazon SageMaker Clarify to generate an EDA report.
Why it's wrong here
Incorrect. SageMaker Clarify is used for detecting bias and explaining model predictions, not for generating EDA reports.
- ✗
Export the results to Amazon QuickSight and create a dashboard.
Why it's wrong here
Incorrect. Amazon QuickSight is for creating interactive dashboards, but it does not include the code or narrative of a notebook.
- ✗
Use Amazon SageMaker Autopilot to generate a report.
Why it's wrong here
Incorrect. SageMaker Autopilot automates machine learning model building and tuning, not EDA report generation.
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
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.
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