Privitar and BigID have partnered to provide organizations with an integrated, automated approach to tackling some of the biggest challenges associated with deriving valuable insights from sensitive data.
The integration of Privitar’s privacy engineering platform and policies with BigID’s data discovery and classification ensures that analytics teams can make use of well-defined, high resolution, de-identified datasets for their programs, and remove manual steps for privacy-aware data pipeline provisioning.
“Timely data access and minimizing privacy risk are critical success factors for today’s data leaders,” said Jason McFall, CTO of Privitar. “The partnership between Privitar and BigID makes both of these possible, enabling enterprises to leverage their data safely and at great speed.“
Today, data engineering and data science teams depend on data derived from multiple sources to drive new insights. Combining data from multiple sources amplifies the risks that individual data subjects are inappropriately profiled or re-identified.
