Data anonymization is the process of modifying personal or sensitive data to remove or mask identifying information, ensuring privacy and compliance with regulations like GDPR and HIPAA. Techniques include data masking, tokenization, and synthetic data generation, making it crucial in AI training, healthcare analytics, and cybersecurity.
Anonymization differs from pseudonymization, which replaces identifiers but keeps a controlled way to re-identify people, and from data tokenization, which keeps a mapping from tokens back to the original values.