Dataguise, a provider of big data security intelligence and protection solutions, announced  the new Dataguise for Data Governance™ suite this week at the Gartner Security and Risk Management Summit. The suite allows organizations to declare policies, discover sensitive data, view and track entitlements, and audit access to sensitive data — automated across transactional databases, data warehouses, file shares, Apache Hadoop, and other Big Data sources.

“With the ever-increasing amounts of data from new and varied sources that can be structured, unstructured and semi-structured, identifying, categorizing and ranking privacy and security risks has become a major challenge in enterprises today,” said Patty Nghiem, vice president of marketing and business development at Dataguise. “With the Dataguise for Data Governance suite, for the first time, organizations who value protecting their data assets have the tools, visibility and automation that are crucial for discovering sensitive data, maintaining compliance, mitigating risk and facilitating data governance — especially given the rise of Big Data initiatives.”

Dataguise Offers New Solution For Big Data Governance

Initial supported platforms include Oracle, IBM DB2, SQL Server, Teradata, Cloudera, Hortonworks, MapR and Pivotal HD. Dataguise for Data Governance is fully compatible with DgSecure, Dataguise’s flagship platform for data privacy, protection and security for sensitive data across the enterprise.

Dataguise for Data Governance features include:

• Policy Quickstart: Select pre-defined policies for PCI, PII and HIPAA; or click-to-create custom policies with no coding or scripting
• Sensitive Data Discovery: Automatically find and track sensitive data in the enterprise, whether at rest or in motion, in structured or unstructured format, across heterogeneous data platforms
• Entitlements: View and track entitlements down to the user and data element level
• Auditing: View automated reports and dashboards to track who accessed what sensitive data

Read more here

(Image credit: Flickr)

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