DEA-C01 Data Security and Governance Practice Question
A data engineer is using AWS Lake Formation to manage access to a data lake in Amazon S3. The engineer needs to grant a specific IAM role read access to only the columns 'customer_id' and 'purchase_amount' in a table stored in the AWS Glue Data Catalog. The table contains sensitive columns like 'credit_card_number'. Which Lake Formation permission model should the engineer use to achieve this?
⚠ Common exam trap
The trap here is thinking that IAM policies can enforce column-level access within Lake Formation, when Lake Formation uses its own permission model with data filters.
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 the IAM role SELECT permission on the table, and then create a data filter that includes only the required columns.
AWS Lake Formation provides fine-grained access control, including column-level security. To grant read access to specific columns, you grant SELECT permission on the table and then attach a data filter that includes only the allowed columns. Data filters are evaluated at query time, ensuring that the role can only access the specified columns. This is the most direct and secure method.
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 IAM role DESCRIBE permission on the table, and then use AWS Glue to create a transformed dataset with only the required columns.
Why it's wrong here
DESCRIBE permission only allows viewing metadata, not reading data. Creating a transformed dataset would duplicate data and not enforce access control on the original table. Lake Formation's column-level security is designed to enforce permissions at query time without data duplication. This approach does not meet the requirement of granting read access to specific columns.
- ✗
Grant the IAM role SELECT permission on the table, and then use an IAM policy to deny access to the sensitive columns.
Why it's wrong here
IAM policies cannot be used to deny access to specific columns in a Lake Formation-governed table. Lake Formation manages fine-grained access control at the table, column, and row level. IAM policies only control access to Lake Formation APIs and the Data Catalog, not the underlying data columns. Thus, this approach will not restrict column access.
- ✓
Grant the IAM role SELECT permission on the table, and then create a data filter that includes only the required columns.
Why this is correct
Lake Formation supports column-level security through data filters. A data filter allows you to specify which columns are included or excluded. By granting SELECT on the table and then creating a data filter that includes only customer_id and purchase_amount, the role can access only those columns. This is the correct way to implement column-level access control in Lake Formation.
- ✗
Create a view in Amazon Athena that selects only the required columns, and grant the IAM role access to the view.
Why it's wrong here
While views can restrict columns, Lake Formation's native column-level security is more integrated and does not require creating separate views. Moreover, if the role has access to the underlying table, it might bypass the view. Lake Formation data filters are the recommended way to enforce column-level permissions directly. Using a view adds complexity and does not leverage Lake Formation's centralized governance.
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 and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.