Anonymization is a data processing technique used to protect individual privacy by removing or altering personally identifiable information (PII) in data sets, ensuring that individuals cannot be identified. It is widely used to facilitate the analysis and sharing of sensitive information, such as medical records or financial data. Anonymization methods include data masking, pseudonymization, and generalization, which transform identifiable data into a form that cannot be traced back to an individual. This allows organizations to use and share data for analysis, research, or public release without compromising data privacy or regulatory compliance.