Quick Answer
The answer is Amazon Athena because it enables you to count duplicates in S3 data using Athena’s standard SQL queries directly against the dataset without any data movement or infrastructure setup. Athena is a serverless interactive query service that uses Presto under the hood, allowing you to run SELECT COUNT(*) with GROUP BY clauses on columns to identify duplicate rows stored in CSV, JSON, Parquet, or other formats in S3. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of which service provides ad-hoc SQL analytics on data lakes versus ETL or cluster-based options. A common trap is confusing Athena with AWS Glue, but Glue is for extract-transform-load jobs, not direct querying; another trap is Redshift Spectrum, which requires a running Redshift cluster. SageMaker Studio is an IDE for ML development, not a query engine. Memory tip: think “Athena = SQL on S3, no cluster needed” — the name itself evokes direct, serverless wisdom.
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 analyst wants to check for duplicate rows in a dataset stored in S3. Which AWS service can be used to run a SQL query to count duplicates without moving the data?
Amazon Athena
Athena can run SQL queries on S3 data to count duplicates.
Amazon Redshift Spectrum
Why wrong: Requires a Redshift cluster, which may be overkill.
Amazon SageMaker Studio
Why wrong: SageMaker Studio is an IDE, not a query service.
AWS Glue
Why wrong: Glue is for ETL, not ad-hoc queries.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Amazon Athena
Option B is correct because Amazon Athena allows running SQL queries directly on data in S3, including counting duplicates. Option A is wrong because AWS Glue is an ETL service, not a query engine. Option C is wrong because Amazon Redshift Spectrum can query data in S3 but requires a Redshift cluster. Option D is wrong because Amazon SageMaker Studio is an IDE, not a query service.
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 this is correct
Athena can run SQL queries on S3 data to count duplicates.
Related concept
Read the scenario before looking for a memorised answer.
Amazon Redshift Spectrum
Why it's wrong here
Requires a Redshift cluster, which may be overkill.
Amazon SageMaker Studio
Why it's wrong here
SageMaker Studio is an IDE, not a query service.
AWS Glue
Why it's wrong here
Glue is for ETL, not ad-hoc queries.
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: Amazon Athena — Option B is correct because Amazon Athena allows running SQL queries directly on data in S3, including counting duplicates. Option A is wrong because AWS Glue is an ETL service, not a query engine. Option C is wrong because Amazon Redshift Spectrum can query data in S3 but requires a Redshift cluster. Option D is wrong because Amazon SageMaker Studio is an IDE, not a query service.
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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