Data Anonymization

Data anonymization is the process of transforming personal data so that individuals cannot be identified - either directly or indirectly - from the resulting dataset. Properly anonymized data falls outside the scope of privacy regulations like GDPR because it no longer constitutes personal data.

Anonymization techniques include generalization (replacing exact values with ranges - age 34 becomes age 30-39), suppression (removing identifying fields entirely), noise addition (slightly perturbing numerical values), and k-anonymity (ensuring each record is indistinguishable from at least k-1 others).

True anonymization is harder than it appears. Research has shown that 'anonymized' datasets can often be re-identified by combining them with other data sources - a property sale record that removes the buyer's name may still be re-identifiable from the combination of address, price, and date. Differential privacy is a more mathematically rigorous approach to anonymization.