MLS-C01 Data Engineering Practice Question
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?
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
✓
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.
Answer analysis
Option-by-option breakdown
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.
- ✗
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.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.