- A
Amazon SageMaker Data Wrangler with a custom transform for text cleaning.
Why wrong: Amazon SageMaker Data Wrangler is designed for data preparation and feature engineering on tabular data, not specifically for text analysis or spell-check. While it can apply custom transforms for text cleaning, it is not the best tool for detecting spelling errors during EDA compared to a purpose-built NLP service.
- B
Amazon Athena with SQL queries to find anomalies.
Why wrong: Amazon Athena allows SQL queries on data in S3. It can find anomalies using patterns or regular expressions, but it is not specialized for text semantics and would require complex queries; it is less suited than Comprehend.
- C
Amazon Comprehend to detect syntax and entities.
Correct. Amazon Comprehend provides syntax analysis and entity detection, which can help identify unusual text patterns (e.g., misspelled words or odd characters) without custom coding. It is the most appropriate AWS AI service among the options for initial text inspection.
- D
Amazon QuickSight to create word clouds.
Why wrong: Amazon QuickSight is a business intelligence tool for creating visualizations. It can generate word clouds from text, but word clouds only show word frequency, not spelling errors or unusual characters. Thus, it is not suitable for this detection task.
MLS-C01 Amazon Comprehend Practice Question
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. A key principle to apply: amazon Comprehend. 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 is working with a dataset that contains text reviews and a numeric rating (1-5). The goal is to predict the rating from the review text. During EDA, the scientist wants to check if there are any spelling errors or unusual characters. Which tool is BEST suited for this task?
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
Amazon Comprehend to detect syntax and entities.
Amazon Comprehend is the best choice among the options because it is an AWS AI service that can detect syntax, entities, and key phrases in text. While it does not directly find spelling errors, it can identify unusual patterns or anomalies in text that may indicate misspellings or odd characters. SageMaker Data Wrangler is for tabular data, Athena is for SQL queries, and QuickSight is for visualization, none of which are specialized for text analysis in this context.
Key principle: Amazon Comprehend
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon SageMaker Data Wrangler with a custom transform for text cleaning.
Why it's wrong here
Amazon SageMaker Data Wrangler is designed for data preparation and feature engineering on tabular data, not specifically for text analysis or spell-check. While it can apply custom transforms for text cleaning, it is not the best tool for detecting spelling errors during EDA compared to a purpose-built NLP service.
- ✗
Amazon Athena with SQL queries to find anomalies.
Why it's wrong here
Amazon Athena allows SQL queries on data in S3. It can find anomalies using patterns or regular expressions, but it is not specialized for text semantics and would require complex queries; it is less suited than Comprehend.
- ✓
Amazon Comprehend to detect syntax and entities.
Why this is correct
Correct. Amazon Comprehend provides syntax analysis and entity detection, which can help identify unusual text patterns (e.g., misspelled words or odd characters) without custom coding. It is the most appropriate AWS AI service among the options for initial text inspection.
Related concept
Amazon Comprehend
- ✗
Amazon QuickSight to create word clouds.
Why it's wrong here
Amazon QuickSight is a business intelligence tool for creating visualizations. It can generate word clouds from text, but word clouds only show word frequency, not spelling errors or unusual characters. Thus, it is not suitable for this detection task.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Candidates might think Amazon Comprehend can detect spelling errors directly, but it does not. It analyzes syntax and entities, which can help identify unusual patterns, but a custom solution or spell-check library would be needed for exact spelling correction.
Trap categories for this question
Command / output trap
Amazon QuickSight is a business intelligence tool for creating visualizations. It can generate word clouds from text, but word clouds only show word frequency, not spelling errors or unusual characters. Thus, it is not suitable for this detection task.
Detailed technical explanation
How to think about this question
Treat this as a scenario question. Identify the problem, the constraint, and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Amazon Comprehend
- Text Preprocessing in EDA
- Syntax Detection
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Amazon Comprehend
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Amazon Comprehend Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Review amazon Comprehend, then practise related MLS-C01 questions on the same topic to reinforce the concept.
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Exploratory Data Analysis — This question tests Exploratory Data Analysis — Amazon Comprehend.
What is the correct answer to this question?
The correct answer is: Amazon Comprehend to detect syntax and entities. — Amazon Comprehend is the best choice among the options because it is an AWS AI service that can detect syntax, entities, and key phrases in text. While it does not directly find spelling errors, it can identify unusual patterns or anomalies in text that may indicate misspellings or odd characters. SageMaker Data Wrangler is for tabular data, Athena is for SQL queries, and QuickSight is for visualization, none of which are specialized for text analysis in this context.
What should I do if I get this MLS-C01 question wrong?
Review amazon Comprehend, then practise related MLS-C01 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Amazon Comprehend
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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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