MLS-C01 Exploratory Data Analysis Practice Question
A company stores customer transaction data in Amazon S3. A data scientist needs to perform exploratory data analysis using Amazon SageMaker. The dataset is 500 GB in CSV format. Which approach is most cost-effective and time-efficient for initial data profiling?
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 Amazon S3 Select to sample rows directly from S3
Amazon S3 Select can query a subset of rows directly from S3 without loading the entire dataset, enabling quick and cost-effective profiling. Option B is incorrect because loading the full 500 GB into a SageMaker notebook instance is expensive and time-consuming. Option C is incorrect because converting to Parquet format adds overhead that is unnecessary for initial profiling. Option D is incorrect because using AWS Glue ETL to transform the entire dataset before analysis is not cost-effective for initial data exploration.
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 Amazon S3 Select to sample rows directly from S3
Why this is correct
S3 Select allows efficient querying of a subset without full data movement.
- ✗
Load the entire dataset into a SageMaker notebook instance and use pandas
Why it's wrong here
Loading 500 GB into memory is impractical and costly.
- ✗
Convert the data to Parquet format and then use Athena to query
Why it's wrong here
Conversion adds overhead; for initial profiling, not needed.
- ✗
Use AWS Glue ETL to transform the data and then analyze in Athena
Why it's wrong here
Glue ETL processes entire dataset, taking time and cost.
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
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.