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Dataguise Powers Data Centric Audit & Protection Platform with Sophisticated Machine Learning

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by Angela Guess

A recent press release states, “Dataguise, a leader in data-centric audit and protection (DCAP), today introduced DgSecure 6.2 at the 2017 Strata Data Conference in New York. The company will showcase its latest DCAP solution at the event, which provides state-of-the-art detection, protection, monitoring, and auditing of sensitive information throughout the enterprise for compliance with a wide range of privacy data regulations — including the General Data Protection Regulation (GDPR). DgSecure is a premier data-centric audit & protection platform that delivers simple, powerful software for sensitive data governance. The out-of-the-box solution deploys quickly and eliminates the need for custom programming, reducing the time, resources, compliance costs and complication of alternative products.”

The release goes on, “The latest generation software extends the breadth and depth of the product and adds enhancements that include: User and entity behavioral analytics and monitoring using sophisticated machine learning algorithms; Support for detection in multiple European languages for GDPR, powered by machine learning; Enhanced feature set for sensitive data detection and protection of Linux and Windows file data; Monitoring support for Google GCS; Sensitive data detection in Google BigQuery; Support for Spark-enabled Hadoop clusters; Support for Apache Tez; SAML integration for enterprise single sign-on, and Robust high availability updates across DgSecure components. ‘Security and risk management leaders must use data-centric audit and protection products to mitigate threats and compliance issues to critical data,’ said Gartner in a recent report titled, Market Guide for Data-Centric Audit and Protection. ‘These products monitor and respond to malicious or inappropriate user access behavior with data stored pervasively across on-premises or cloud silos’.”

Read more at Marketwired.

Photo credit: Dataguise

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