Traditionally, different data stakeholders had to contend with different and incompatible views of their data assets.

  • Privacy professionals like CPOs and DPOs relied on interviews and surveys to build inventories of personal data.
  • Security professionals used pattern based classification technologies inside three letter products like DLP, DRM and DAM designed in the mid 2000’s to find sensitive data in either file folders, mail or SQL databases.
  • Data governance professionals depended on metadata catalogs that ingested column names from databases, data lakes and relational data warehouses to help map what type of data resided in what tables

Besides the fact that none of the approaches were compatible with one-another, each also presents arguably insurmountable problems toward achieving the goal of providing authoritative data truth and trust in data.

  • Privacy-based data surveys (as opposed to scans) rely on data recollections instead of data records making them imprecise and error prone by definition.
  • Pattern-based data classification technologies can’t disambiguate similar looking data, can’t map data to an owner and lack data coverage in terms of modern data sources.
  • Governance based metadata catalogs, only provide a narrow lens into a modern data landscape, and can only surface what a developer wrote in a column header without validation against the column content.

BigID transforms how organizations see and understand their data, providing the first-of-its-kind Discovery-in-Depth technology to look at data four ways in order to provide the data content and content necessary for privacy, security and governance.

With BigID, organizations can create a single source of data truth, without compromising the views necessary for a CPO, CSO or CDO to conduct their business.