To improve analytics performance, hardware matters, too. Allan Hackney, CIO at the insurance and financial services giant John Hancock, is adding GPU chips-the same graphical processors found in gaming systems-to his arsenal. "The math that goes into visualizations is very similar to the math that goes into statistical analysis," he says, and graphics processors can perform calculations hundreds of times faster than conventional PC and server processors. "Our analytic people love this stuff."
3. Technology Costs Less
Along with increases in computing capacity, analytics are benefitting from falling prices for memory and storage, along with open source software that provides an alternative to commercial products and puts competitive pressure on pricing.
Ternent is an open-source evangelist. Prior to joining Island One, he was vice president of engineering for Pentaho, an open-source business intelligence company, and worked as a consultant focusing on BI and open source. "To me, open source levels the playing field," he says, because a mid-sized company such as Island One can use R, an open-source application, instead of SAS for statistical analysis.
Once, open-source tools were available only for basic reporting, he says, but now they offer the most advanced predictive analytics. "There is now an open-source player across just about the entire continuum, which means there's tooling available to whoever has the gumption to go and get it."
HMS' Nustad sees the changing economics of computing altering some basic architectural choices. For example, one of the traditional reasons for building data warehouses was to bring the data together on servers with the computing horsepower to process it. When computing power was scarcer than it is today, it was important to offload analytic workloads from operational systems to avoid degrading the performance of everyday workloads. Now, that's not always the right choice, Nustad says.
"With hardware and storage so cheap today, you can afford to juice up those operational systems to handle a BI layer," she says. By factoring out all the steps of moving, reformatting and loading data into the warehouse, analytics built directly on an operational application can often provide more immediate answers.
Hackney observes, however, that although the price performance trends are helpful for managing costs, potential savings are often erased by increased demands for capacity. "It's like running in place," he says. While John Hancock's per unit cost for storage dropped by 2 to 3% this year, consumption was up 20%.
4. Everyone's Mobile
Like nearly every other application,