Anonymization is the process of removing or altering personal information from data sets so that individuals cannot be easily identified. This technique is commonly used in fields like healthcare and research to protect privacy while still allowing for data analysis. By replacing identifiable information with pseudonyms or aggregating data, organizations can share valuable insights without compromising individual privacy. There are various methods of anonymization, including data masking, encryption, and generalization. Each method has its strengths and weaknesses, depending on the type of data and the intended use. Effective anonymization helps maintain confidentiality while enabling the use of data for analysis and decision-making.