MLS-C01 Exploratory Data Analysis Practice Question
A data scientist is starting a new machine learning project and needs to understand the dataset. The dataset is stored as CSV files in Amazon S3, with a total size of 50 GB. The data scientist wants to quickly get summary statistics (count, mean, standard deviation, min, max) for each numerical column, and also check for missing values. The data scientist has access to SageMaker Studio. What is the most efficient way to achieve this?
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 SageMaker Data Wrangler to import the data and generate a data quality report.
SageMaker Data Wrangler is purpose-built for data preparation and profiling, allowing you to compute summary statistics and check for missing values with a visual interface and without writing code. Option A (AWS Glue Crawler + Athena) only infers schema and enables SQL queries; it does not automatically provide summary statistics or missing value counts. Option B (PySpark script) is possible but requires manual coding and Spark cluster management, making it less efficient for quick exploration. Option C (Amazon QuickSight) is a BI tool that requires loading data into SPICE, which is not as streamlined for initial data profiling as Data Wrangler.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use AWS Glue Crawler to infer schema and then query with Athena.
Why it's wrong here
Crawler does not compute statistics.
- ✗
Write a PySpark script in a SageMaker notebook to compute statistics.
Why it's wrong here
More work than necessary.
- ✗
Load a sample into Amazon QuickSight and use SPICE to compute statistics.
Why it's wrong here
Requires importing data into QuickSight.
- ✓
Use SageMaker Data Wrangler to import the data and generate a data quality report.
Why this is correct
Data Wrangler provides summary statistics and missing value analysis.
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
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 →
Same concept, more angles
1 more way this is tested on MLS-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Which AWS service can be used to generate a data profile (including histograms, correlations, and statistics) for a dataset stored in Amazon S3 without writing code?
easy- A.Amazon QuickSight
- B.AWS Glue DataBrew
- C.Amazon Athena
- ✓ D.Amazon SageMaker Data Wrangler
Why D: Amazon SageMaker Data Wrangler provides a visual interface for data profiling without code. AWS Glue DataBrew also offers similar profiling capabilities, but Data Wrangler is the native SageMaker tool, making it the expected answer for this exam. QuickSight is for visualization, not profiling, and Athena is for querying.
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.