Data anonymization is the process of removing or altering personally identifiable information from a dataset in order to protect the privacy of individuals. This involves replacing sensitive data, such as names, addresses, and social security numbers, with random or pseudonymous values, making it impossible to identify specific individuals from the data. The purpose of data anonymization is to balance the need for data analysis and sharing with the protection of personal privacy. It is often used in research, healthcare, and business settings to ensure compliance with privacy laws and regulations. By anonymizing data, organizations can still gain valuable insights and make informed decisions without compromising the privacy of individuals.