DATAGUISE CLOSES $13 MILLION SERIES B FINANCING TO CAPITALIZE ON MULTI-BILLION DOLLAR BIG DATA MARKET Sep 30, 2013
Investors Back Dataguise to Deliver New Era of Security and Data
Protection Solutions to Enable Secure Leverage of Big Data Assets
FREMONT, Calif., September 30, 2013 – Dataguise (http://www.dataguise.com), a leading innovator of data security intelligence and protection solutions, today announced that it has closed a $13 million Series B funding round led by Toba Capital with additional capital coming from the investment arm of a leading electronic conglomerate. Dataguise will utilize the financing to further expand global sales, marketing, channel development, and support efforts, as well as ongoing innovation of its DgSecure™ suite of products which allow businesses to achieve a 360-degree view of their sensitive data assets across Big Data and traditional data repositories.
“Having Toba Capital and other investors participate in our success will be instrumental as we enter the next phase of rapid growth and continued product innovation that is changing the dynamics of securing privacy data in Hadoop,” said Manmeet Singh, CEO, Dataguise. “This round of financing gives us additional runway to execute further with our growing family of channel partners and end customers, while extending our technical capabilities and aggressively expanding our footprint and market reach worldwide.”
Complementing this round of financing, industry veterans Vinny Smith and Paul Sallaberry have been appointed to the Dataguise Board of Directors. Both members add a wealth of knowledge and industry expertise as the company executes on its next stage of growth and innovation. Smith launched Toba Capital in 2012 to invest in leading edge business applications and Internet infrastructure companies after selling Quest Software to Dell for $2.4 billion. Paul Sallaberry served in senior operating roles in highly-regarded technology companies for nearly 30 years and was responsible for growing Veritas from less than $50 million in sales to more than $1.5 billion.His ability to help early-stage companies grow from modest levels of revenue to tremendous scale is best-in-class.
“Ensuring the security of sensitive data will become a growing concern for enterprise CIOs as they leverage Big Data for operational and analytical use cases,” said John L. Myers, Senior Analyst for Business Intelligence, Enterprise Management Associates –a Boulder, CO based analysis and consulting firm. “With a proven product suite, deployment strategy and financial backing, Dataguise promises to establish itself as a significant category participant in the emerging area of Big Data security.”
“Dataguise has all the components for success including a white-hot market opportunity, a disruptive platform for discovering, protecting and assessing the risk of sensitive data exposure and is well positioned to put its competition on the defensive,” said Vinny Smith, founder, Toba Capital. “The company is in an excellent position to deliver highly differentiated and adaptive solutions for its customers and partners to deliver on the promise of Big Data.”
According to IDC’s most recent worldwide Big Data technology and services market forecast1 the worldwide Big Data technology and services market will grow at a 31.7% compound annual growth rate (CAGR) –about seven times the rate of the overall information and communication technology (ICT) market –with revenues reaching $23.8 billion in 2016.
Dataguise Sets Standard for a New Era of Security and Data Protection for Big Data Organizations globally are exploring the advantages of Hadoop and its ability to enable the analysis of data patterns previously inaccessible. However, compliance and security officers are mindful of the sensitive information located in these large data repositories and the lack of controls to prevent unauthorized access. Traditional approaches to securing Hadoop fail because they are too complex, expensive, and incapable of selectively protecting the data that matters in these large and diverse environments. DG for Hadoop™ provides an efficient, economical and effective method of determining where and how to secure sensitive data in Hadoop.
DG for Hadoop, part of the DgSecure™ suite of products, identifies the unique characteristics of Big Data, processing multiple terabytes of structured, unstructured and semi-structured data in only a few hours to protect sensitive data at the source, during ingestion and in the Hadoop Distributed File System (HDFS). Key features available in the latest generation software include:
Contextual-based data discovery: The Dataguise contextual-based data discovery capability uses a “neural-like network” approach for highly accurate sensitive data search instead of a simple “rule-based” approach. As a result, information surrounding a given string is correlated and complex inferences are made to determine whether that string is relevant to the search.
Selective encryption: Complementing Dataguise masking technology for configurations where data mining needs to operate on actual data values. DG for Hadoop uses symmetric key based encryption of data and also encrypts the encryption keys themselves for stronger security.Consistent masking across a single or multiple Hadoop clusters: This capability preserves analytical value of information for trend analysis and aggregations.
Simplified management: DG for Hadoop provides automatic notifications so that security personnel can be alerted by e-mail or SMS when a job is completed or when changes occur.
Compliance audit reports: New reporting that compliance auditors can integrate in their analysis of the company’s overall compliance process and posture.
Dataguise is the leading provider of data privacy protection and compliance intelligence for sensitive data assets stored in both Big Data and traditional repositories. Dataguise’s comprehensive and centrally managed solutions allow companies to 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.
1 IDC, Worldwide Big Data Technology and Services 2012-2015 Forecast (IDC #233485)