Analytics on a compute grid?

Analytics programs have become an increasingly important tool for many companies to help provide insight into how the business is performing. The need to measure performance and gauge ROI across lines of business has been particularly important during the global recession over the past two years. At the same time, the amount of data that companies amass daily and must process to analyze performance has exploded. As a result, analytics programs are becoming increasingly bloated, expensive and difficult to run within many organizations.

This problem is due in part to the fact that a lot of analytics are running on legacy environments (including Hardware, software, processes). These environments are very expensive to own and maintain in terms of both CapEx and OpEx. Given the markets trends of huge increase in data volumes and users and analytical models requiring near real-time service level agreements (SLA), these legacy systems have become very expensive and are beginning to hinder, rather than enable, the growth of business. Furthermore, scalability and performance issues are also beginning to hinder ease of adoption and use for BI tools.

What is the alternative? Running the analytics applications on a compute grid comprised of commodity hardware. This enables the adoption of a lower cost, higher performance approach by simplifying the environment and making it easier for users to move to model. Rather than overtaxing legacy systems, grid solutions allow you to make the most of the systems you already have in place. Grid provides high availability, lower costs and virtually unlimited scalability.

Platform Symphony is the leading grid management middleware solution that enables embarrassingly high parallelization of high performance compute and data intensive applications using policy based grid management that enforces application service levels. Platform Symphony also manages a shared pool of resources to meet the dynamic demands of multiple applications, enabling enterprise-class availability, security, and scalability and providing maximum utilization across large, diverse pools of resources.