Pseudonymization

Big Data Privacy Anonymization and Pseudonymization Big data projects often mix millions of records with personal hints. Protecting privacy is essential for user trust and regulatory compliance, but teams still need useful insights. Anonymization and pseudonymization are two core tools to balance privacy and analytics. What they mean Anonymization removes identifiers that can link a record to a real person. It also reduces or hides indirect clues that could help identify someone. Pseudonymization replaces direct identifiers with a stable token. The same person can still be linked across datasets if allowed, but the real name stays hidden. ...