Software

Chicago, IL, October 6, 2003 -- SPSS Inc. (Nasdaq: SPSS), the leading provider of predictive analytics, today announced the immediate availability of Clementine� 8.0, the latest version of its widely used data mining workbench. This latest version of Clementine was developed based on input from technical data miners and is designed to enable them to quickly prepare data, build and rapidly compare models, and immediately deploy models into real-time operational environment. Clementine 8.0 also adds capabilities to its already open design that enable easiy integration with business systems, such as operational customer relationship management (CRM) systems.

Clementine 8.0, which supports the full data mining process and provides a visual map of data mining steps, features new data manipulation nodes that include binning and reclassification capabilities for faster data preparation. A new data audit feature enables data miners to quickly assess all of their data. Visualization enhancements include a cluster viewer, which enables analysts and non-analyst users to explore and understand clusters, and more flexible model evaluation features for quick model understanding. Clementine 8.0 extends its in-database mining capability to include model scoring and bulk data loading, further leveraging the underlying performance and management capabilities of enterprise database environments.

To assist analysts in quickly distributing Clementine output to decision makers in their organization, SPSS is launching a Web deployment tool called Cleo(tm) (Clementine online). Cleo, which is designed for easy and quick model deployment over the Web, enables multiple users to access Clementine output and score data on an ad hoc basis. The deployment tool provides capabilities to score a single input record, multiple records, or an entire database.

The Richmond, Virginia Police Department's criminal analysis group relies on Clementine's intuitive, visual data mining process to analyze local crime data. Finding patterns and relationships in raw crime data allows the department to characterize and predict violent crime as well as confidently connect seemingly random, independent incidents. Then using Cleo, operational police personnel can access these predictive models in real-time over the Department's intranet. Front-line personnel, such as detectives, can make potentially life-saving decisions by receiving immediate predictive analytic results via Cleo's simple Web-based prompts and pull down menus.

For further information, please visit www.spss.com