Last week, TOP500 announced that IBM POWER Sequoia supercomputer at Lawrence Livermore National Laboratory (LLNL) is ranked the world’s most powerful computing system. Sequoia is made up of 96 racks of the IBM Blue Gene/Q system – a platform that IBM specifically designed to help organizations like LLNL solve large-scale scientific and societal problems that make our world smarter. As someone who helped build our Blue Gene system business earlier in my IBM career, I feel a sense of personal pride that this new system achieved record-breaking performance.
Power Systems line of servers and industrial-strength, highly secure virtualization technologies, we are helping businesses of all sizes deliver new services faster with higher quality and superior economics.
A prime example of this is in the area of business analytics. In today’s fast-paced marketplace, simply managing information is no longer enough. Companies need to make decisions quicker than ever before and those decisions must be based on facts. Data can provide those facts, but with vast amounts of data available from many sources – such as transaction records of credit card purchases, posts to social media sites, or cell phone GPS signals – it can be overwhelming. Some organizations are finding that there is simply too much data, and too little time and resources to make sense of it all.
Business analytics solutions can help organizations examine that vast amount of data quickly to spot trends and anomalies, and make it actionable through predictive modeling. More insight into current and target customers is an opportunity for every business to build loyalty and gain competitive advantage. The key is implementing a system that enables people to be proactive, rather than reactive, about customer demands and shifts in the marketplace.
Just as a supercomputer can compute trillions of calculations per second when its system is tuned to the scientific task at hand, business analytics software that runs on a server platform that’s optimized for that purpose can really make a distinct performance difference. You can also significantly lower your total computing costs by taking a workload optimized approach to business analytics systems design versus a “one-size fits all” approach.
Turning information into world-changing insights is not just the domain of complex scientific projects. Your organization’s success does not necessarily require the ability to carry out 16 quadrillion calculations a second. What it needs is to be smarter – about the computing systems it uses to anticipate and react to your customers’ needs. In this way, you could say that business analytics has become the equivalent of high performance computing for everyday businesses. Because making computing smarter is beneficial for organizations of every size.