More and more organisations plan to use analytical prediction to make profitable strategic decisions on issues as diverse as optimal cellphone mast placement or in-store shelf space allocation.
"Too often, however, the desire for an analytical understanding of data collected in hugely expensive IT systems is hamstrung by previous choices of non-standard information repositories and computing platforms," says Annemarie Cronje, solution architect at SAS Institute, leaders in business intelligence.
"Often the quest for analytics to underpin prediction is restricted by IT's inability to integrate data from different hardware and software sources, and then to use this data for modelling and forecasting."
When choosing advanced analytics software, therefore, it is important to invest in solutions that achieve analytical insights regardless of existing infrastructure.
"It is essential to choose an analytical toolset that can be used with any hardware platform and data repository in the enterprise," says Cronje. She advises businesses to look for flexible options that allow leverage of current hardware and data storage investment, and provide avenues for growth.
SAS can access data regardless of whether it resides in spreadsheets or hierarchical and relational databases. It provides fast, efficient loading of data from and to these facilities, working directly from these sources without making copies.
"Co-existence and interoperability are among SAS's major strengths," says Cronje.
For organisations wanting to introduce advanced analytics, but lacking good storage capability, SAS also offers extensible, platform-independent storage options that provide repositories and computing power to suit different business needs while making the most of existing resources.
In SAS 9, to be launched in late March, interoperability is further enhanced, and, according to Cronje, the new version is altogether more "sexy" than its predecessor.
"SAS has become Web-based, making it easy to extend power to more users," she says. "The offering is fully scalable, as well as interoperable. Manageability and usability are easy. In addition, much functionality is wizard-driven, allowing users to pull in whatever they need, without having to worry about coding.
"This means, for example, that users can pull real-time forecasting into their Word documents."
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