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MetricStream Adds Big Data Analytics Support For Enhanced Risk Intelligence

GRC Platform Supports Hadoop and MongoDB Big Data Frameworks to Enhance Risk and Compliance Management

MetricStream, a provider of Governance, Risk, and Compliance (GRC) solutions on Thursday announced its capability to leverage Big Data analytics in order to provide greater visibility and transparency into an organization's overall risk profile.

The company said that by adding the Big Data analytics functionality, customers will be able to better manage the increasing volume, velocity, and variety of data, which will help them in overall in their risk management and regulatory compliance challenges.

Big Data Analytics in Risk Management“Threat and vulnerability data from numerous security solutions, social and digital media content violating corporate policies and regulations, supply chain incidents spreading virally on the web that damage reputation, and transaction trends indicating a financial fraud or illegal activity can be more easily identified and managed as a result of big data analytics,” the company explained in a statement. “Through collecting and analyzing large and disparate data points, trends begin to emerge, thereby enabling reactive discovery of incidents and proactive identification of emerging issues.”

On the technical side, MetricStream’s GRC platform supports Apache's Hadoop, an open source framework for processing large data sets in a distributed computing environment, and MongoDB, a NoSQL database system.

In order to collection data from various source across the enterprise, the platform uses “Infolet integration technology”, an agent-based architecture for distributed data extraction, processing, and delivery. Infolet adaptors integrate with big data sources to capture relevant information and include it within MetricStream GRC applications for processing, routing, and reporting, the company said.

According to the Palo Alto, California-based company, customers can now tackle “massive volumes of structured and unstructured data including transactions, trades, social media and multimedia content, weblogs, security logs, geo-location data, click streams and email text.” Once collected, the large datasets can be incorporated into their risk assessment, analysis, mitigation, and reporting processes.