Quick Answer
The answer is AWS Glue DataBrew, which should be used to compute summary statistics efficiently because it offers a no-code visual interface for profiling datasets directly from Amazon S3, automatically generating statistics like mean, median, and standard deviation for numeric columns with minimal setup. This is the correct choice because DataBrew is purpose-built for data preparation and profiling, eliminating the need to write SQL queries in Athena, manage clusters in EMR, or configure SageMaker Data Wrangler for simple exploratory analysis. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of the fastest path to data profiling during exploratory data analysis, often appearing as a trap where candidates overcomplicate the solution by choosing SageMaker Data Wrangler or Athena. The key distinction is that DataBrew is the most efficient for quick, code-free summary statistics, while Data Wrangler excels when you need to build complex transformation pipelines. Memory tip: think “Brew for the view”—DataBrew gives you a visual brew of your data’s stats instantly.
This MLS-C01 practice question tests your understanding of exploratory data analysis. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 machine learning engineer is performing exploratory data analysis on a large dataset stored in Amazon S3 using AWS Glue. The dataset contains a mix of numeric and categorical features. The engineer wants to efficiently compute summary statistics (e.g., mean, median, standard deviation) for the numeric columns. Which AWS service or feature should the engineer use to achieve this with minimal setup?
Launch an Amazon EMR cluster and use Spark.
Why wrong: EMR requires cluster setup and management.
Use AWS Glue DataBrew to profile the dataset.
DataBrew provides an easy interface for profiling and statistics.
Use Amazon Athena to run SQL queries on the data.
Why wrong: Athena requires writing SQL queries and is less automated.
Use Amazon SageMaker Data Wrangler.
Why wrong: Data Wrangler is powerful but more complex for simple statistics.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use AWS Glue DataBrew to profile the dataset.
Option B is correct because AWS Glue DataBrew provides a visual interface to profile data and compute summary statistics without writing code. Option A is wrong because Amazon Athena requires SQL queries and more manual effort. Option C is wrong because Amazon EMR requires cluster setup and management. Option D is wrong because Amazon SageMaker Data Wrangler is a good tool but requires more configuration than DataBrew for simple summary statistics.
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.
Launch an Amazon EMR cluster and use Spark.
Why it's wrong here
EMR requires cluster setup and management.
Use AWS Glue DataBrew to profile the dataset.
Why this is correct
DataBrew provides an easy interface for profiling and statistics.
Related concept
Read the scenario before looking for a memorised answer.
Use Amazon Athena to run SQL queries on the data.
Why it's wrong here
Athena requires writing SQL queries and is less automated.
Use Amazon SageMaker Data Wrangler.
Why it's wrong here
Data Wrangler is powerful but more complex for simple statistics.
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.
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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: Use AWS Glue DataBrew to profile the dataset. — Option B is correct because AWS Glue DataBrew provides a visual interface to profile data and compute summary statistics without writing code. Option A is wrong because Amazon Athena requires SQL queries and more manual effort. Option C is wrong because Amazon EMR requires cluster setup and management. Option D is wrong because Amazon SageMaker Data Wrangler is a good tool but requires more configuration than DataBrew for simple summary statistics.
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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