What best describes data anonymization and when is it used?

• A. Removing or masking identifying data to protect privacy while enabling analysis.
• B. Storing raw identifiers for audit trails.
• C. Encrypting data so it cannot be analyzed.
• D. Providing full identifiers to external partners.

Answer: (A)

Data anonymization means removing or masking identifying data so the information can be used for analysis without exposing who the individuals are. This approach protects privacy by eliminating direct identifiers (like names or IDs) or replacing them with non-identifiable substitutes, while preserving enough detail for meaningful analytics. It’s used whenever you need to analyze or share data that includes personal information but you want to prevent re-identification, such as in research, reporting, or public data releases. The other options describe storing raw identifiers, encrypting data, or sharing full identifiers, none of which achieve anonymization or privacy-safe analysis.