Dataguise Upgrades Data Discovery, Masking Solutions

PRESS RELEASE

Fremont, CA, Via Oracle OpenWorld San Francisco, CA & SC World Congress New York City, NY., October 12, 2009 " dataguise (http://www.dataguise.com), a leading innovator of security solutions for protecting sensitive data across the enterprise, today announced the next generation of the company's popular dataguise security solution - dgdiscover 3.0 and dgmasker 3.0. Version 3.0 is the industry's first integrated solution for comprehensive sensitive data discovery and masking. It is designed to find structured database repositories across the network, search and discover sensitive data in structured databases, and then mask or de-identify to protect sensitive data.

With dataguise, organizations now have access to a single product that finds, searches and masks sensitive data across all databases throughout the enterprise. This allows organizations to create corporate masking policies for faster adherence to compliance regulations, lower risk of a data breach, and reduced reliance on cumbersome singledatabase masking solutions.

"Sensitive data stored in non-production databases are exposed to abuse or negligence from outsiders but mostly from enterprise employees. Potential abusers, whom data masking aims to deter, are mainly users of test databases (programmers, testers and database administrators)," says Dr. Joseph Feiman, Research Vice President and Gartner Fellow. "Adopting data masking will help enterprises raise the level of security and privacy assurance against insiders' and outsiders' abuses. At the same time, data masking will make enterprises compliant with the security and privacy standards recommended by regulating/auditing organizations."

Find IT, Search IT, and Mask IT.

In many organizations, sensitive information is scattered in unprotected databases and file servers across corporate infrastructure.

Although most enterprises have taken measures to control access to critical data in their production environments this protection does not always extend to non-production data. Enterprises are continuously cloning production data to support development, testing, QA and pre-production deployment. As a result, sensitive data can be inadvertently propagated throughout the extended enterprise. This can include employee data such as Taxpayer IDs, employee names/addresses, and dependent information, customer information such as credit cards and card expiration dates, and intellectual property or classified information. The need to satisfy requirements for regulations such as, HIPAA, PCI and PII as well as data theft prevention and sound governance make it imperative that organizations implement the necessary processes to block exposure of this sensitive information. The first step is finding the databases containing the sensitive data.

Leading organizations, including Amgen (Nasdaq: AMGN), Facebook, John Muir Hospital, and the University of California Berkeley have turned to dataguise as their partner in the protection against sensitive information loss or theft. dataguise offers the first integrated product offering of its kind to combine both discovery of databases containing sensitive data, identification of the data at risk in the database and Masking In Place (MIP) of the information for seamless security. dgdiscover 3.0 empowers these organizations by quickly determining where sensitive information resides throughout the enterprise and dgmasker 3.0 then de-identifies information targeted for use outside of the production network.

dataguise provides a high level of automation to deliver fast and reliable discovery without extensive management overhead. Unlike alternative offerings, the solution was developed to be simple and user friendly, resulting in a relatively low dependency on professional services for implementation and support. Both dgdiscover and dgmasker scale for use in small and medium size enterprises to the largest multi-national corporations for unlimited enterprise-wide discovery and masking.

Additional benefits of dgdiscover and dgmasker: