What is data anonymization used for?

• A. Removing or obfuscating identifiers to prevent re-identification in analytics.
• B. Removing all data entirely
• C. Replacing data with random numbers only
• D. Encrypting data with keys in transit

Answer: (A)

Data anonymization is used to protect privacy in analytics by removing or obfuscating identifiers so the data can’t be linked back to individuals. By stripping direct identifiers (like names or IDs) and, if needed, generalizing or masking other details, you can analyze patterns and trends without exposing who the data belongs to. This enables data sharing and analysis while reducing re-identification risk and helping meet privacy requirements. The other options don’t fit because removing all data eliminates value; replacing with random numbers alone can distort meaning and may not effectively protect privacy; and encrypting data in transit protects data during transfer but doesn’t make the released data anonymous for analytical use.