Description: Data sanitization is the process of cleaning and preparing datasets for analysis or use by removing sensitive or irrelevant information. This process is crucial in data management as it ensures that shared or processed information does not compromise individuals’ privacy. Sanitization involves identifying and removing personally identifiable information (PII), such as names, addresses, and identification numbers, as well as correcting errors and normalizing formats. By performing effective sanitization, organizations can comply with data protection regulations, such as GDPR in Europe, and foster user trust when handling their information. Additionally, data sanitization allows analysts to work with cleaner and more relevant data, improving the quality of analyses and data-driven decisions. In a world where privacy and information security are increasingly important, data sanitization becomes an essential practice for any entity handling sensitive information.
