KDnuggets : News : 2008 : n03 : item9 < PREVIOUS | NEXT >

Software


Subject: SAS supercharges predictive analytics

SAS achieves record $2.15 billion revenue (February 5, 2008)

SAS in leaders' quadrant for business intelligence platforms (February 4, 2008)

SAS supercharges predictive analytics (February 4, 2008)

CARY, NC (Feb. 05, 2008) - SAS, the leader in business intelligence, has significantly enhanced its award-wining SAS Enterprise Miner(tm), SAS Text Miner, and SAS Forecast Server software, bringing predictive analytics to their highest level yet.

The newest release of SAS Enterprise Miner improves productivity through added interactive advanced visualization and new analytics. Fifteen new analytical tools improve the resulting predictive models, which can mean significant savings for customers with proactive marketing departments such as in retail or banking. With innovative new modeling algorithms, including gradient boosting, partial least squares and support vector machines, SAS Enterprise Miner users can build more stable and more accurate models and thus make better decisions faster and with more confidence.

  • Unstructured data from customer feedback forms, blogs, call centers and other sources is now incorporated even more easily in SAS Text Miner. Combining that with SAS Enterprise Miner's improved ability to visualize analytical results, SAS Text Miner quickly discovers and exploits patterns that would otherwise remain hidden in stored business documents. Bringing these new insights to decision makers can create a significant competitive advantage.
  • SAS Forecast Server's new release includes user interface enhancements that provide greater control. There are now more outlier detection options, more complex filtering capability, and six new statistics of fit. Over a dozen new project management macros help handle routine project management tasks more effectively in batch mode. And performance and scalability improvements allow SAS Forecast Server to work even more efficiently with very large data sets - decreasing the time needed for decisions.
For more information, visit www.sas.com

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