The correct combination includes Amazon Macie, AWS CloudTrail, and AWS Lake Formation. Amazon Macie uses machine learning to automatically discover and classify sensitive data such as customer PII within your S3 data lake, fulfilling the sensitive data discovery requirement. AWS CloudTrail logs all API calls to the S3 bucket, providing the necessary access logging and monitoring. AWS Lake Formation then enables data anonymization through its fine-grained access controls, allowing you to apply column-level masking or tokenization so that sensitive data is anonymized before being shared with external partners. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your ability to integrate security, logging, and governance services for a compliant data lake, with a common trap being to overlook Lake Formation’s anonymization role in favor of S3 server access logs. Remember the mnemonic “MCL” for Macie (discovery), CloudTrail (logging), and Lake Formation (anonymization) to quickly recall the trio.
DEA-C01 Data Security and Governance Practice Question
This DEA-C01 practice question tests your understanding of data security and governance. 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 engineer is configuring a data lake on Amazon S3 that contains sensitive customer information. The company requires that all access to this data be logged and monitored, and that any data shared with external partners must be anonymized before leaving the S3 bucket. Which combination of AWS services should the engineer use to meet these requirements? (Choose THREE.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
AWS Lake Formation
AWS Lake Formation (B) is correct because it provides fine-grained access control and data anonymization capabilities for data lakes on Amazon S3. It allows you to define column-level and row-level security policies, and can automatically anonymize sensitive data (e.g., via masking or tokenization) before it is shared with external partners, ensuring compliance with data governance requirements.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 WAF
Why it's wrong here
WAF is for web application firewall, not data logging or anonymization.
✓
AWS Lake Formation
Why this is correct
Lake Formation provides fine-grained access control and can be used to enforce anonymization policies.
Related concept
Read the scenario before looking for a memorised answer.
✓
AWS CloudTrail
Why this is correct
CloudTrail logs API calls to S3, meeting logging requirement.
Related concept
Read the scenario before looking for a memorised answer.
✗
AWS Direct Connect
Why it's wrong here
Direct Connect is a network connection service, not for security governance.
✓
Amazon Macie
Why this is correct
Macie discovers sensitive data, helping identify what needs anonymization.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse AWS WAF (a web-layer security tool) with data-level security, or assume Direct Connect provides logging and monitoring, when in fact neither service addresses S3 data access logging or anonymization.
Detailed technical explanation
How to think about this question
Under the hood, Lake Formation integrates with AWS Glue to catalog data and applies policies via AWS IAM and S3 bucket policies, enabling row-level security using partition projection and column-level security via view-based masking. For anonymization, it can use AWS Glue ETL jobs with custom transforms (e.g., hashing, redaction) or leverage Amazon Macie for sensitive data discovery before applying policies. In a real-world scenario, a healthcare company could use Lake Formation to mask patient names and SSNs in a shared dataset while preserving analytical value.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
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
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Data Security and Governance — This question tests Data Security and Governance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: AWS Lake Formation — AWS Lake Formation (B) is correct because it provides fine-grained access control and data anonymization capabilities for data lakes on Amazon S3. It allows you to define column-level and row-level security policies, and can automatically anonymize sensitive data (e.g., via masking or tokenization) before it is shared with external partners, ensuring compliance with data governance requirements.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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This DEA-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 DEA-C01 exam.
Question Discussion
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