DA0-002 Data Governance Practice Question
A payroll analyst receives a spreadsheet of employee compensation and needs to share aggregate salary statistics with an external benchmarking vendor. Which action best aligns with data minimization principles?
⚠ Common exam trap
The trap here is equating any privacy-protective technique, such as encryption or pseudonymization, with data minimization even though the underlying row-level data is still disclosed.
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
✓
Send only the calculated aggregates, such as median and quartile salaries by job family
Data minimization requires that personal data processing and disclosure be limited to what is adequate, relevant, and necessary for the purpose. The benchmarking vendor needs statistics, not records, so computing aggregates by job family removes individual exposure while meeting the business need. Techniques that merely obscure or protect row-level data, such as pseudonyms, encryption, or partial redaction, leave unnecessary personal data in scope.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Encrypt the spreadsheet with a shared password and email the password in a separate message
Why it's wrong here
Encryption protects confidentiality in transit but does not reduce the volume or sensitivity of data disclosed. The vendor would still hold full individual compensation records, violating the principle that only necessary data should be shared. Encrypting an over-broad dataset addresses a different control objective, so it does not satisfy data minimization for this scenario.
- ✗
Replace employee names with randomly generated identifiers before sending the file
Why it's wrong here
Pseudonymizing names reduces direct identifiability but retains full compensation records at the individual level. The vendor only needs aggregate statistics, so sending row-level pay data with swapped identifiers still over-shares personal information beyond the stated purpose. Data minimization calls for limiting collection and disclosure to what is necessary, which this approach does not achieve.
- ✓
Send only the calculated aggregates, such as median and quartile salaries by job family
Why this is correct
Data minimization means disclosing only the personal data necessary for the stated purpose. Since the vendor needs aggregate salary statistics, providing computed aggregates by job family eliminates exposure of individual compensation records entirely. This satisfies the benchmarking need while removing the risk of re-identification or misuse of row-level payroll data, making it the strongest alignment with the principle.
- ✗
Redact Social Security numbers and bank account fields, then send the remaining compensation rows
Why it's wrong here
Redacting selected sensitive fields lowers risk but still discloses individual salary amounts tied to role and tenure, which can be identifying in small job families. Because the vendor's purpose is aggregate benchmarking, row-level disclosure remains broader than necessary. This option reduces but does not eliminate over-sharing, so it falls short of the minimization standard.
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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 CompTIA exam blueprint
This DA0-002 practice question is part of Courseiva's free CompTIA 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 DA0-002 exam.