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Dataguise Positioned in "Visionaries" Quadrant of the Gartner Magic Quadrant for Data Masking Technology

Evaluation Based on Completeness of Vision and Ability to Execute

FREMONT, CA -- (Marketwired) -- 12/23/13 -- Dataguise, a leading innovator of data security intelligence and protection solutions, today announced that Gartner, Inc., a leading IT research and advisory firm, has positioned Dataguise in the "Visionaries" quadrant of the December 2013 Magic Quadrant for Data Masking Technology(1).

Tweet This: Need #BigData, #Hadoop data security? @Gartner_Inc calls @Dataguise #Visionary in 2013 Data Masking #MQ (LINK) #infosec #datasecurity

Gartner analysts Joseph Feiman and Brian Lowans wrote in the Data Masking Technology report that, "Data masking has emerged to address relational databases as well as mainframe databases and files. Currently, in response to demand, the market has begun offering SDM [static data masking] and DDM [dynamic data masking] for big data platforms."

The report recommends that enterprises, "Engage key enterprise stakeholders -- especially in risk management, privacy, compliance and auditing roles -- in the adoption and implementation of data masking processes," and that the "adoption of data masking is also being driven by regulatory requirements and mandates, such as PCI Data Security Stands (DSS) and HIPAA. Application development outsourcing is another main factor that is accelerating data masking adoption, because data masking can ensure that enterprises' sensitive data will not be exposed to ESPs' developers."

Manmeet Singh, co-founder and CEO, Dataguise, said, "Sensitive data is being compromised every day, not just from outsider attacks but also via insider threats. With the ever-increasing privacy and compliance mandates that our customers must adhere to, plus the emergence of Big Data and new technologies such as Hadoop, the urgency to discover and protect sensitive data has intensified." He continued, "Our Global 2000 customers recognize Dataguise as a leader in Big Data protection. We believe our positioning as a Visionary in Gartner's Magic Quadrant for Data Masking Technology demonstrates our commitment to deliver leading-edge, easy-to-deploy technologies for data masking, which are an integral part of our DgSecure solutions."

Dataguise is a pioneer in Hadoop data masking for Cloudera, Hortonworks, MapR, Greenplum and InfoSphere BigInsights. Dataguise provides solutions addressing data discovery, protection and compliance for a wide range of industries and enterprise operations. DgSecure, DG for Hadoop, DBMS, Microsoft SharePoint and Files allows even the most-targeted organizations, such as those within the financial services industries, to protect Social Security numbers, payment card information (PCI), personally identifiable information (PII), and corporate IP.

For the latest news and information about the Big Data and Hadoop data security landscape, socialize with Dataguise:

About Dataguise
Dataguise is the leading provider of data privacy protection and compliance intelligence solutions for sensitive data stored in Hadoop, Big Data and traditional data repositories. Dataguise's comprehensive and centrally managed solutions allow companies to discover and maintain a 360-degree view of their sensitive data, evaluate their compliance exposure risks, and enforce the most appropriate remediation policies, whether the data is stored on premises or in the cloud. For more information, visit www.dataguise.com.

Disclaimer:
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

(1) Gartner "Magic Quadrant for Data Masking Technology" by Joseph Feiman and Brian Lowans, 12 December 2013.

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