The term data anonymization entails the process of removing or altering personally identifiable information (PII) from datasets. This is done to protect individuals' privacy while still allowing data to be utilized for analysis or research. Anonymization methods might include masking, aggregation, or perturbation, ensuring that data cannot be traced back to an individual. This practice is crucial for compliance with data protection regulations such as GDPR and HIPAA, balancing privacy with the need for data insights.