SAS SUPERCHARGES PREDICTIVE ANALYTICS

Fifteen new analytical tools for improved predictive models

Sydney (February 21, 2008) – SAS, the leader in business intelligence, has significantly enhanced its award-wining SAS Enterprise Miner™, 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 visualisation 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, rapid deployment options, and comprehensive model management capabilities, SAS analytics users can build, deploy, and monitor even greater numbers of more stable and more accurate models, helping to make better decisions faster and with more confidence.

Talking of the enhancements, Evan Stubbs, SAS Australia and New Zealand’s solution manager for Analytics, said, “The practical advantages of these additions to SAS’s analytical tools can’t be overstated. Not only do they demonstrate SAS’s commitment to best practice in analytics, they also cement our status as the only vendor with a truly integrated platform designed to deliver business benefit from the ground up.” He continued, “Only SAS has the capability and commitment to its customer base to ensure that analytics aren’t just a buzzword or something conducted in the back office, divorced from the enterprise. Effective, actionable use of analytics is the fastest way of measuring and increasing corporate business performance.”

Unstructured data from customer feedback forms, blogs, call centres and other sources can now be incorporated even more easily in SAS Text Miner. Combining that with SAS Enterprise Miner’s improved ability to visualise 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 and maintain a significant competitive advantage.

SAS Forecast Server’s new release includes user interface enhancements that provide greater control. With even more outlier detection options, more complex filtering capability, and six new statistics of fit, SAS Forecast Server truly represents best practice in automatic forecasting. 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. With SAS, organisations can decrease the time needed for good decisions without needing to compromise.

In this release, the new analytic tools and productivity enhancements for analysts are another sign of SAS' commitment to its continued leadership of the advanced analytics software market," said Dan Vesset, Vice President, Business Analytics research, IDC. "Advanced analytics tools for predictive and descriptive analytics are a key component of providing organisation with better decision-making capabilities that can lead to competitive advantage."

Quick problem solving can save millions. The SAS Enterprise Intelligence Platform’s “integration by design” streamlines data mining and forecasting by building in required data integration and metadata pre-processing steps before beginning advanced analytics. With SAS data integration, storage, analytics and business intelligence all working together, the guidance resulting from analytics will be available sooner, helping decision makers uncover timely insights.

Using the SAS Enterprise Intelligence Platform as a foundation, SAS offers targeted business solutions that support enterprise intelligence, customer intelligence, financial intelligence, supply chain intelligence and more – as well as turnkey solutions for vertical markets, such as telecommunications, financial services, health care, retail, manufacturing and others.

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