INDUSTRY

SAS today delivered SAS(R)9 to users worldwide, complete with a new platform, enhanced analytics and refined user interfaces that provide fresh insights for solving business problems and driving competitive advantage. This software marks the most significant release in SAS' 28-year history. SAS(R)9 is faster, more efficient and easier to use than its predecessors. It can accommodate changing organizational needs without any loss of efficiency. The new platform connects all SAS applications so they work together transparently, and it also communicates with other data sources and programs. SAS(R)9 includes the SAS Intelligence Platform, a broad set of integrated software for unmatched data integration, easy-to-use business reporting and unparalleled analytics. It also boasts enhancement of the most tightly integrated optimization and predictive analytics capabilities available, making it even easier to answer complex questions that cannot be addressed by traditional business intelligence (BI). "For years, SAS has been known as the industrial-strength analytics standard of choice," said Jim Goodnight, president and CEO of SAS. "SAS(R)9 delivers the depth and breadth of enterprise BI that goes far beyond traditional query and reporting to deep analytics - which is where most BI vendors stop short. The SAS Intelligence Platform gives organizations the decision-making confidence they need to meet regulatory compliance requirements and other business needs." Discover insights with powerful analytics SAS(R)9 analytics are part of an integrated, scalable, high-performance platform that gives executives unprecedented foresight, allowing them to anticipate the changing needs of the organization. Enhanced analytics in SAS(R)9 include a comprehensive set of capabilities like predictive and descriptive modeling, forecasting, simulation, optimization, and design of experiments. SAS(R)9 takes full advantage of analytical advances, equipping users with additional and enhanced predictive modeling capabilities, PMML scoring code to ease deployment on analytics, and a Web-based model repository to enable reusability.