Data discovery and data classification are foundational for privacy and governance programs. But traditional methods are problematic.
Manual surveys and spreadsheets are incomplete and immediately out-of-date. And they're not integrated with privacy software, making risk assessments, ROPAs, and PIAs difficult.
Today’s privacy landscape is complex enough. Modern privacy programs require efficient and dynamic data discovery that flexibly connects to data sets and AI models, offers centralized control, and enables privacy use cases such as data subject rights fulfillment, security controls, records of processing, and risk assessments.
Read more: What is data mapping?
