What is redaction and tokenization of PII in datasets?

Redaction and tokenization are methods of protecting personally identifiable information (PII) in datasets.

Redaction is the process of removing or hiding sensitive information from data, such as replacing a name or passport number with symbols like "****" or deleting the data entirely. This helps prevent personal information leaks during data analysis or publication.

Tokenization involves replacing real PII with unique, but meaningless tokens (substitutes) that do not reveal the original data but allow maintaining the structure and relationships within the dataset. For example, a credit card number is replaced with a random token that can be used for analysis but cannot be directly linked to the real number without a special mapping table.

Both methods are important for complying with confidentiality and security requirements when working with sensitive data, especially in machine learning and analytics.