DEA-C01 Data Security and Governance Practice Question
A data engineer manages an Amazon Redshift cluster that contains a table with credit card numbers. The security team requires that the credit card column be stored in encrypted form and that only users with a specific IAM role can see the full values. Other users should see a partially masked value when they query the table. Which Redshift feature should the data engineer use?
⚠ Common exam trap
The trap here is assuming that column-level encryption also masks values for unauthorized users, when it only protects data at rest.
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
✓
Redshift dynamic data masking with a masking policy attached to the credit card column.
Redshift dynamic data masking attaches a masking policy to a column and evaluates the querying user's role at query time. Authorized roles see the original value, while others see a masked form such as the last four digits. Column-level encryption, Spectrum, and row-level security address different concerns and cannot produce role-based partial masking of a column value.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Redshift row-level security with a policy that filters rows containing credit card numbers.
Why it's wrong here
Row-level security filters which rows a user can see based on a policy, but it does not mask column values. A user either sees the entire row, including the full credit card number, or does not see the row at all. Partial masking of a column value is not possible with row-level security, so it does not satisfy the requirement.
- ✗
Redshift column-level encryption with a customer managed key in AWS KMS.
Why it's wrong here
Redshift column-level encryption encrypts data at rest for specified columns, but it does not provide dynamic masking based on the querying user's IAM role. All users who can select the column see the decrypted value. It also requires managing keys and does not produce a partially masked value for unauthorized users, so it does not meet the visibility requirement.
- ✗
Redshift Spectrum with an external table that uses a SerDe to mask the credit card column.
Why it's wrong here
Redshift Spectrum queries data stored in Amazon S3 through external tables, not data stored in Redshift local tables. A SerDe controls serialization and deserialization of external data and does not implement role-based masking. This approach would require moving the data out of Redshift and would not provide the required user-specific visibility control.
- ✓
Redshift dynamic data masking with a masking policy attached to the credit card column.
Why this is correct
Redshift dynamic data masking applies a masking policy to a column so that unauthorized users see a masked value at query time, while authorized roles see the full value. It is role-based and does not require changing the stored data. This directly satisfies the requirement to show partial values to most users and full values only to a specific role.
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JA
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.