ML-driven Data Governance Suite is launching at Gartner’s Data & Analytics Summit 2021

BigID, the leading data intelligence and management platform for privacy, protection, and perspective, today announced the release of the Data Governance Suite, a new set of apps designed to reimagine data governance – which will be featured at the Gartner Data & Analytics Summit, May 4-6, 2021.

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For far too long, data teams have struggled to get accuracy and efficiency with their data governance platforms. Catalogs have lacked context, coverage, and scale. Data stewards are burdened with heavily-manual data curation. Quality engineers struggle to get detailed KPIs across all their data.

BigID reimagines data governance as a modern data-driven, ML-infused, open and extensible platform. The BigID data governance suite of apps are built on a discovery-in-depth foundation that can find and manage metadata at scale across any data type. The core catalog leverages ML for labeling and discovery, plus deeper insights into data values, neighboring data relationships and locations of duplicate or similar data.

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On top of the foundational data catalog and discovery, BigID provides a series of core Governance Apps that can be added modularly to automate data management:

• Data Stewardship that replaces manual curation processes with ML-based validation activities
• Data Glossary that can automate the building of logical data definitions from physical data
• Data Quality that compounds column analytics with first-of-its-kind attribute-level quality analytics

In addition, BigID provides a growing marketplace of BigID and third-party Apps in privacy, security, and data lifecycle management that can be added on-demand to extend BigID’s governance capabilities in infinite ways on the same platform.

“Data governance – because ultimately, it’s about the data – needs to begin with the data,” said Dimitri Sirota, CEO and co-founder of BigID. “Our new data governance suite starts from the data up, reimagining how organizations manage their data: with automation, deep context, and improved accuracy and efficiency for data management teams so that they can get more value from their data.”

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