IBM hardware and software solutions drill deep to help companies handle big data faster
Illustration by Andy Potts
Sometimes big data isn’t measured in terabytes or even petabytes. Instead, it’s measured by the heartbeat of tiny premature infants in neonatal intensive care units. Numerous sensors monitor each of these newborns on a regular basis, tracking temperature, respiration rates and other vital information. Doing so results in massive amounts of data that can be used by doctors to proactively manage the babies’ health.
Healthcare is by no means the only industry that uses big data to achieve desired outcomes. Credit card companies, retailers and others also glean information from large amounts of data and analyze that data to make business decisions, according to Dan Olds, principal, Gabriel Consulting Group. IBM Systems Magazine, Power Systems* edition sat down with Olds and Chuck Bryan, IBM PowerLinux* Strategy and Business Development manager, to learn how IBM and PowerLinux solutions can help companies take advantage of the opportunities afforded by big data.
IBM Systems Magazine: What does big data mean to business?
Dan Olds: I think big data, which has become an overarching term covering a lot of important ground, is the next big thing for business. It’s sort of evolutionary, but the effect it’s had and is going to continue to have will be revolutionary. This isn’t just another trend; it’s real and it’s not going away. It’s like the Ghost of Christmas Future. Big data and analytics-led decision making are going to be the basis of normal competition down the road.
Big data isn’t about technology. This isn’t a tech-driven fad; it’s driven by macroeconomics. Globalization has given us the ability to do business across borders. Logistics enable us to reach into every part of the world. Vendors and manufacturers can source products anywhere in the world and get them sent anywhere else in the world. Everybody has something to sell. Everybody is competing with pretty much everybody else. It’s bordering on perfect competition, which puts all of the power right in the hands of buyers.
ISM: How do companies compete in this kind of environment?
DO: Wall Street traders, for example, all have the same financial instruments and tools to use. They all have the same data, too. There’s only so much data out there you can use legally. In that kind of intense, competitive environment, they develop trading algorithms and models that drive their decisions. If the price of gold does this and interest rates do that, they will buy or sell these stocks at these prices. Those trading algorithms are their crown jewels—that data is their most important asset. Wall Street has been there for two decades.
A large discount retailer is another example. The retailer tracks the cold and flu season as it moves across the country to make sure they have enough tissue and cold pills in the right stores at the right time. This means they don’t have to buy 20 percent more cold medicine during cold and flu season. They buy the same amount, but they make sure it’s in the places where it’s needed so they don’t run out of stock. That’s the kind of advantage you can get out of analytics.
In terms of where we are from a technical standpoint, we’ve gotten to a point where the expertise is available—along with the hardware and software—to allow companies to take advantage of big data.
The economy is such that companies that want to compete and thrive are going to have to use big data and predictive analytics to do so. In this competitive environment, something new and innovative gives you the ability to make a nice profit until someone else tries to do the same thing. They either copy you or do you one better—by selling a better version of what you’re selling cheaper or delivering it to the market faster. Then you’ve got to come up with the next innovation. We’ve always been in that environment, but with the globalization and the Internet, those cycles happen much quicker.
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