The answer is to use AWS Glue DataBrew’s data quality and missing data reports. This is correct because DataBrew provides a dedicated missing data report that automatically generates heatmaps, bar charts, and correlation matrices to visualize patterns of missingness, allowing you to distinguish between MCAR, MAR, and MNAR without writing any code. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your ability to choose the right tool for exploratory data analysis versus heavy transformation—a common trap is reaching for SageMaker Data Wrangler, which lacks built-in missingness pattern analysis, or assuming Athena can handle this task when it is only for querying. Glue ETL jobs require custom coding and are inefficient for quick pattern exploration, making DataBrew the most efficient choice for a 5 TB dataset. Memory tip: think “Brew for the view”—DataBrew gives you a visual brew of missing data patterns, while other tools leave you coding from scratch.
MLS-C01 Exploratory Data Analysis 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. 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 analyzing a dataset with a large number of missing values in several columns. The dataset is stored in an Amazon S3 bucket and is about 5 TB in size. The scientist wants to understand the pattern of missingness (e.g., is it missing completely at random, missing at random, or not missing at random) before deciding on an imputation strategy. The scientist has access to AWS Glue DataBrew and Amazon SageMaker Studio. Which approach should the scientist take to best understand the missing data patterns?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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's data quality and missing data reports
AWS Glue DataBrew provides a missing data report that includes patterns and correlations of missingness, such as heatmaps and bar charts. This helps determine the type of missingness. Option B is wrong because SageMaker Data Wrangler does not have built-in missingness pattern analysis. Option C is wrong because Athena is for querying, not pattern analysis. Option D is wrong because Glue ETL jobs require custom coding and are less efficient for exploratory 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
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Use Amazon SageMaker Data Wrangler to create a flow and analyze missingness visually
Why it's wrong here
Data Wrangler does not have specific missingness pattern analysis; it's more for transformations.
✓
Use AWS Glue DataBrew's data quality and missing data reports
Why this is correct
DataBrew's reports visualize missing data patterns and correlations.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
✗
Use AWS Glue ETL jobs with PySpark to compute missingness statistics
Why it's wrong here
Custom coding is required and not as straightforward as DataBrew's built-in reports.
✗
Use Amazon Athena to run queries to find missing values per column
Why it's wrong here
Athena can find counts but not patterns of missingness.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
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
How to think about this question
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.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
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
How this comes up in practice
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
Got this wrong? Here's your next step.
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 — This question tests Exploratory Data Analysis — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Use AWS Glue DataBrew's data quality and missing data reports — AWS Glue DataBrew provides a missing data report that includes patterns and correlations of missingness, such as heatmaps and bar charts. This helps determine the type of missingness. Option B is wrong because SageMaker Data Wrangler does not have built-in missingness pattern analysis. Option C is wrong because Athena is for querying, not pattern analysis. Option D is wrong because Glue ETL jobs require custom coding and are less efficient for exploratory analysis.
What should I do if I get this MLS-C01 question wrong?
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.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.