~ Co-authored by Steve Conway, Dan Vesset and Earl C. Joseph, Ph.D. ~
More organizations than ever are treating their data as a critical asset that can create competitive advantage by delivering greater insights into customer behavior, operations, financial performance and risk management. These organizations are also learning that they can out-compete their rivals by out-computing them – not just in transaction volumes and the timely analysis of data for decision support, but also by being able to answer more complex questions.
In today’s environment of growing data volumes and shrinking IT budgets, analytical and IT groups both are being tasked with developing and deploying increasingly sophisticated analytical models more quickly. At the same time, hardware requirements for analytical processing have grown so rapidly that they have overwhelmed the capabilities of symmetric multiprocessing (SMP) servers.
As a result, organizations are turning more often to parallelized business analytics solutions that run in high-performance computing environments. The lower costs of technologies such as clusters, grids and cloud computing are encouraging organizations to use these resources for more in-depth and granular business analytic solutions.
This IDC paper focuses on the value of deploying business analytics solutions on grid computing platforms. It discusses high-performance computing environments, the evolution from clusters to grids to cloud computing, the reasons for choosing business analytics software on grid computing platforms and the benefits organizations are achieving with these approaches.
The included case studies illustrate how business analytics along with grid computing and other high-performance computing environments can enable competitive differentiation, even with increasing data volumes, ever-changing decision-support requirements and pressure on IT departments to do more with less.
Download the White paper: Raising the bar on business analytics: innovation powered by grid