Dataguise Unveils Version 3.0 of its Datamasking Security Suite

Dataguise, a provider of security solutions for protecting sensitive data across the enterprise, has announced a new version of its dataguise security suite-dgdiscover 3.0 and dgmasker 3.0. Version 3.0 is an integrated solution for comprehensive sensitive data discovery and masking, designed for file and structured database repository search across the network, discovery of sensitive data within those repositories and masking or de-identification of the data to protect against exposure and risk. With dataguise, organizations now have the ability to create corporate masking policies that allow faster adherence to compliance regulations, lower risk of a data breach, and reduced reliance on cumbersome single-database masking solutions.

According to the vendor, In most organizations, sensitive information is scattered in unprotected databases and file servers across corporate infrastructure, and this is especially true of non-production data environments for testing and other uses that are copied from operational, production databases. The new dataguise security suite combines the discovery of the non-production databases that contain sensitive data, identification of the data at risk in those databases and Masking In Place (MIP) of the information for seamless security.

"The dgdiscover component of the suite quickly determines where sensitive information resides throughout the enterprise and the dgmasker component then de-identifies the information targeted for use outside of the production network," Allan Thompson, senior vice president of business development, marketing, and product strategy at Dataguise, tells 5 Minute Briefing. "The de-identification process creates fictitious information that looks real to the internal systems which need to use it, but is worthless to outsiders. The two components of the suite are separate products that interoperate and can be centrally controlled."

Some of the specific new features of the suite include fast sensitive data discovery across file and structured data repositories, including Oracle, DB2, SQL Server, MySQL, Teradata, Sybase, MS Access, and SharePoint; security for data in both production and non-production environments; adaptive to standard PCI, HIPAA, and other compliance regulations; robust reporting to reflect the threat level of sensitive data; automated, policy-based operation with intelligence that provides recommendations on a variety of topics such as which files, tables and columns to mask; and utilization of Masking in Place (data cloning and masking within the production network) versus less secure solutions that extract data from the more secure production network, then mask.

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