Data anonymization is a type of process to remove sensitive information to enable privacy protection. By removing personally identifiable information from data sets, people whom the data describe remain anonymous.
Example of use
Data anonymization may enable the transfer of information across a boundary, such as between two departments within an agency or between two agencies, while reducing the risk of unintended disclosure.
Subscribe to our newsletter to get the latest from Datastory’s Global Edition.