Quick Answer
The answer is AWS Glue DataBrew, as it is the only AWS service purpose-built for automated data profiling that generates schema, data types, and quality statistics with visualizations directly from datasets in Amazon S3. DataBrew’s profiling engine automatically computes column-level metrics like null counts, value distributions, and data type inferences, enabling data scientists to quickly assess dataset health without writing code. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your ability to distinguish between services that prepare data (DataBrew) versus those that query, store, or visualize it—a common trap is confusing Athena’s schema-on-read with DataBrew’s active profiling, or assuming Redshift’s ANALYZE command provides the same visual output. Remember the memory tip: “Brew profiles, Athena queries, Redshift stores, QuickSight boards.”
This MLS-C01 practice question tests your understanding of exploratory data analysis. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data scientist needs to profile a large dataset in Amazon S3 to understand its schema, data types, and quality. Which AWS service can automatically generate a data profile with statistics and visualizations?
Amazon Athena
Why wrong: Athena is a query service, not profiling.
AWS Glue DataBrew
DataBrew can profile data and generate statistics.
Amazon QuickSight
Why wrong: QuickSight is for visualization after data is prepared.
Amazon Redshift
Why wrong: Redshift is a data warehouse.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
AWS Glue DataBrew
AWS Glue DataBrew provides data profiling capabilities. Option B is wrong because Athena is a query service. Option C is wrong because Redshift is a data warehouse. Option D is wrong because QuickSight is for visualization after data is prepared.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Amazon Athena
Why it's wrong here
Athena is a query service, not profiling.
AWS Glue DataBrew
Why this is correct
DataBrew can profile data and generate statistics.
Related concept
Read the scenario before looking for a memorised answer.
Amazon QuickSight
Why it's wrong here
QuickSight is for visualization after data is prepared.
Amazon Redshift
Why it's wrong here
Redshift is a data warehouse.
Common exam traps
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Exploratory Data Analysis — study guide chapter
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FAQ
Exploratory Data Analysis — This question tests Exploratory Data Analysis — Read the scenario before looking for a memorised answer..
The correct answer is: AWS Glue DataBrew — AWS Glue DataBrew provides data profiling capabilities. Option B is wrong because Athena is a query service. Option C is wrong because Redshift is a data warehouse. Option D is wrong because QuickSight is for visualization after data is prepared.
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Read the scenario before looking for a memorised answer.
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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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