Quick Answer
The answer is Amazon QuickSight and Amazon SageMaker Data Wrangler. QuickSight is correct because it natively supports geospatial charts, such as map-based visualizations, and temporal analysis through time-series line charts, making it ideal for plotting latitude, longitude, and timestamps together. SageMaker Data Wrangler is correct because it allows you to visualize geospatial data as scatter plots directly within its data preparation interface, enabling quick pattern checks before modeling. On the AWS Certified Machine Learning Specialty exam, this question tests your ability to distinguish between visualization tools and unrelated AWS services like Amazon Comprehend (NLP) or Amazon Rekognition (image/video). A common trap is to overlook Data Wrangler’s built-in visualization capabilities, assuming it only handles data transformation. Remember the memory tip: “QuickSight maps the where and when, while Wrangler scatters the coordinates.”
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 is working with a dataset that contains geolocation coordinates (latitude and longitude) and timestamps. The scientist wants to visualize the data to check for spatial and temporal patterns. Which TWO AWS services can be used for this visualization?
Amazon Comprehend
Why wrong: NLP service.
Amazon SageMaker Data Wrangler
Can create scatter plots with coordinates.
Amazon Rekognition
Why wrong: Image/video analysis.
Amazon QuickSight
Supports geospatial and time-series visualization.
AWS Glue
Why wrong: ETL service.
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 SageMaker Data Wrangler
Options B and D are correct. Amazon QuickSight supports geospatial charts and time-series. Amazon SageMaker Data Wrangler can also visualize geospatial data as scatter plots. Option A is wrong because Amazon Comprehend is for NLP. Option C is wrong because AWS Glue is for ETL. Option E is wrong because Amazon Rekognition is for image/video analysis.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Amazon Comprehend
Why it's wrong here
NLP service.
Amazon SageMaker Data Wrangler
Why this is correct
Can create scatter plots with coordinates.
Related concept
Static NAT maps one inside address to one outside address.
Amazon Rekognition
Why it's wrong here
Image/video analysis.
Amazon QuickSight
Why this is correct
Supports geospatial and time-series visualization.
Related concept
Static NAT maps one inside address to one outside address.
AWS Glue
Why it's wrong here
ETL service.
Common exam traps
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
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. NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated. 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
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
Exploratory Data Analysis — study guide chapter
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FAQ
Exploratory Data Analysis — This question tests Exploratory Data Analysis — Static NAT maps one inside address to one outside address..
The correct answer is: Amazon SageMaker Data Wrangler — Options B and D are correct. Amazon QuickSight supports geospatial charts and time-series. Amazon SageMaker Data Wrangler can also visualize geospatial data as scatter plots. Option A is wrong because Amazon Comprehend is for NLP. Option C is wrong because AWS Glue is for ETL. Option E is wrong because Amazon Rekognition is for image/video analysis.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
Static NAT maps one inside address to one outside address.
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Same concept, more angles
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A data scientist needs to understand the distribution of a continuous variable in a large dataset stored in Amazon S3. Which AWS service is most appropriate for quickly generating summary statistics and visualizations?
easyWhy C: Option A is correct because Amazon QuickSight integrates with S3 and can generate histograms and summary statistics without needing to move data. Option B is wrong because SageMaker is for model building, not quick ad-hoc analysis. Option C is wrong because Athena is for querying, not visualization. Option D is wrong because Glue is for ETL, not analysis.
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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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