Question

A healthcare analytics team wants to share a de-identified copy of a patient dataset with external researchers. An 'age' column contains exact ages that, combined with ZIP code and gender, could re-identify individuals. Analysts still need to perform statistical analysis across broad age groups (0-17, 18-64, 65+). The team must transform the data using Sensitive Data Protection (DLP) while preserving analytic utility. Which de-identification transformation should they apply to the age column?

Accepted Answer

Apply a bucketing transformation to generalize ages into the defined ranges

Answer

Apply deterministic cryptographic tokenization (crypto deterministic) to the age values

Answer

Apply date-shift transformation with a fixed shift value to the age column

Answer

Apply a redaction transformation that removes the age column entirely