AIF-C01 Practice Question: Security, Compliance, and Governance for AI Solutions
A company uses AWS Lake Formation to manage data lakes for analytics. They want to ensure that only authorized users can access specific columns in a table containing sensitive data used for ML training. Which Lake Formation feature should they use?
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
✓
Column-level permissions
Lake Formation column-level permissions allow fine-grained access control to specific columns within a table.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Row-level security filters
Why it's wrong here
Row-level security filters restrict which rows a principal sees, not which columns, so they cannot hide sensitive columns in the table. They are tempting because they are a genuine Lake Formation data-filter feature, and would be correct if the requirement were to limit access by row values such as region or tenant.
- ✗
Cell-level security
Why it's wrong here
Cell-level security in Lake Formation applies row and column filter expressions together, but the stem asks specifically for restricting columns, which Lake Formation delivers through column-level security (LF-Tags or named column filters). Cell-level security is tempting because it sounds granular, yet it addresses combined row-and-column masking rather than pure column exclusion.
- ✗
S3 bucket policies
Why it's wrong here
S3 bucket policies govern access at the bucket or prefix level and cannot enforce column-level restrictions within a table's schema. They are tempting because they are the standard AWS access-control mechanism for object storage, and would be correct if the requirement were to restrict access to whole datasets or prefixes rather than individual columns.
- ✓
Column-level permissions
Why this is correct
Column-level permissions in Lake Formation grant or deny access to individual columns within a table, so users querying sensitive ML training data see only authorised fields. This satisfies the requirement to restrict access to specific columns rather than the whole table.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-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 AIF-C01 exam.