MLS-C01 Exploratory Data Analysis Practice Question
Which TWO of the following are best practices for exploratory data analysis when using Amazon SageMaker Data Wrangler? (Select TWO.)
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
✓
Use Data Wrangler's built-in data visualizations to explore feature distributions and relationships.
Data Wrangler's built-in visualizations allow for quick exploration of feature distributions and relationships without leaving the tool, making it a best practice for EDA. Exporting the Data Wrangler flow as a Jupyter notebook enables reproducibility and sharing with the team. Storing intermediate results in Athena (A) is not a best practice specific to Data Wrangler; it adds overhead. Using EMR for data profiling (C) is unnecessary since Data Wrangler includes profiling capabilities. Exporting data to QuickSight before transformation (D) is not recommended; analysis should be done within Data Wrangler's transformation steps.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Store all intermediate results in Amazon Athena for querying.
Why it's wrong here
Athena is not needed for intermediate results; Data Wrangler manages state.
- ✓
Use Data Wrangler's built-in data visualizations to explore feature distributions and relationships.
Why this is correct
Built-in visualizations enable quick EDA.
- ✗
Use Amazon EMR to run Spark jobs for data profiling.
Why it's wrong here
Data Wrangler provides profiling without needing EMR.
- ✗
Always export the data to Amazon QuickSight for analysis before transformation.
Why it's wrong here
QuickSight is not necessary; Data Wrangler has its own analysis tools.
- ✓
Export the Data Wrangler flow as a Jupyter notebook to share with the team.
Why this is correct
Exporting as a notebook promotes reproducibility.
Go deeper
Related to this question
About these practice questions
This MLS-C01 question is part of Courseiva's 1,672-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.