DEA-C01 Data Security and Governance Practice Question
A company is using AWS Lake Formation to manage permissions on a data lake. They want to grant a data scientist the ability to query tables in the 'analytics' database using Amazon Athena, but prevent them from accessing the underlying S3 data directly. What is the best way to achieve this?
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
✓
Grant SELECT permission on the 'analytics' database tables in Lake Formation.
Lake Formation grants SELECT permission on named database tables, which allows querying via Athena without granting direct S3 access. Option A is incorrect because granting s3:GetObject on the entire bucket would allow the data scientist to bypass Lake Formation and access the data directly. Option C is incorrect because a policy that allows Athena queries only does not grant the necessary permissions to access the database tables. Option D is incorrect because adding the user to a data lake location with read access is too broad and would also grant direct S3 access, which does not meet the requirement of preventing direct S3 access.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Grant the data scientist an IAM policy with s3:GetObject on the S3 bucket.
Why it's wrong here
Granting s3:GetObject lets the data scientist read objects directly, defeating the goal of Lake Formation-mediated access. Direct S3 IAM permissions are correct when bypassing Lake Formation is intended, but here table-level grants through Lake Formation are required.
- ✓
Grant SELECT permission on the 'analytics' database tables in Lake Formation.
Why this is correct
Lake Formation grants SELECT on the analytics tables, letting the data scientist query them through Athena while Lake Formation mediates access to the underlying S3 objects. Direct S3 access stays blocked because permissions are enforced at the catalog and table level, not through S3 bucket policies.
- ✗
Create an IAM policy that allows Athena queries only.
Why it's wrong here
An Athena-only IAM policy does not grant Lake Formation table permissions, so queries fail; Lake Formation enforces its own grants independently of IAM. IAM-only policies suit environments without Lake Formation, but here the data scientist needs Lake Formation SELECT grants on the analytics tables.
- ✗
Add the data scientist to a Lake Formation data lake location with read access.
Why it's wrong here
Granting a Lake Formation location read access exposes the underlying S3 objects, so the data scientist could bypass Athena and read the bucket directly. Location permissions are for controlling raw S3 data access, and would be the right choice when a principal must query files directly rather than only through Athena tables.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.