Quick Answer
The answer is AWS Glue DataBrew. DataBrew is a visual data preparation tool that includes built-in transformations for data masking, allowing you to obfuscate sensitive columns like PII or financial data without writing any code. While AWS Glue Studio can build ETL jobs, it lacks native masking functions, requiring custom scripts. AWS Lake Formation handles fine-grained access control at the table or column level but does not transform the underlying data values, and Amazon Macie only discovers sensitive data rather than masking it. On the MLS-C01 exam, this question tests your understanding of AWS Glue’s ecosystem and the distinction between data masking (altering values) and access control (restricting visibility). A common trap is confusing Lake Formation’s column-level permissions with actual masking, or assuming Glue Studio includes masking as a built-in step. Remember: if you need to change the data itself to protect sensitive fields, think DataBrew—it’s the only service in the Glue family that offers one-click masking.
This MLS-C01 practice question tests your understanding of data engineering. 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 company needs to process sensitive data from multiple sources. They want to use AWS Glue to catalog and transform the data. Which feature should they use to ensure that sensitive columns are masked before the data is available for querying?
AWS Glue DataBrew
DataBrew allows data masking and cleansing interactively.
AWS Glue Studio
Why wrong: Glue Studio builds ETL, but masking requires custom transforms.
AWS Lake Formation
Why wrong: Lake Formation controls access at row/column level but doesn't mask.
Amazon Macie
Why wrong: Macie discovers sensitive data but doesn't mask.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
AWS Glue DataBrew
Glue DataBrew provides data masking and cleansing capabilities. Glue Studio is for building ETL jobs, but masking requires custom code. Lake Formation is for fine-grained access control, not masking. Macie is for discovering sensitive data, not masking.
Key principle: Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
AWS Glue DataBrew
Why this is correct
DataBrew allows data masking and cleansing interactively.
Related concept
CIDR notation defines the prefix length.
AWS Glue Studio
Why it's wrong here
Glue Studio builds ETL, but masking requires custom transforms.
AWS Lake Formation
Why it's wrong here
Lake Formation controls access at row/column level but doesn't mask.
Amazon Macie
Why it's wrong here
Macie discovers sensitive data but doesn't mask.
Common exam traps
Subnetting questions often tempt you into counting all addresses. In normal IPv4 subnets, the network and broadcast addresses are not usable host addresses.
Detailed technical explanation
Subnetting questions test whether you can identify the network, broadcast address, usable range, mask and correct subnet. Slow down enough to calculate the block size correctly.
Key takeaway
Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
Real-world example
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related MLS-C01 subnetting questions on CIDR, address ranges, and subnet selection.
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FAQ
Data Engineering — This question tests Data Engineering — CIDR notation defines the prefix length..
The correct answer is: AWS Glue DataBrew — Glue DataBrew provides data masking and cleansing capabilities. Glue Studio is for building ETL jobs, but masking requires custom code. Lake Formation is for fine-grained access control, not masking. Macie is for discovering sensitive data, not masking.
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related MLS-C01 subnetting questions on CIDR, address ranges, and subnet selection.
CIDR notation defines the prefix length.
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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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