Advances in analytic technologies and business intelligence are allowing CIOs to go big, go fast, go deep, go cheap and go mobile with business data.
Current trends center as much on tackling analytics challenges as they do on taking advantage of opportunities for new business insights. For example, technologies for managing and analyzing large, diverse data sets are arriving just as manyorganizations are drowning in data and struggling to make sense of it. Still, many of the cost and performance trends in advanced analytics mean companies can ask more complicated questions than ever before and deliver more useful information to help run their businesses.
In interviews, CIOs consistently identified five IT trends that are having an impact on how they deliver analytics: The rise of big data, technologies for faster processing, declining costs for IT commodities, proliferating mobile devices and social media.
Technology Costs Less
Along with increases in computing capacity, analytics are benefiting 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 Hancock’s per unit cost for storage dropped by 2 to 3 percent this year, consumption was up 20 percent.
No comments:
Post a Comment