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Clementine 9.0, the latest version of the award-winning data mining workbench from SPSS Inc, leverages its open, standards-based architecture to offer explicit integration with Oracle Database 10g, the first relational database designed for Grid computing. Oracle Database 10g supports predictive modeling with Oracle Data Mining, enabling the building and scoring of models directly within the database. "Since we implement large data mining projects, GIP has long been a proponent of this sort of integration," said Alexander Ebbes of GIP Exyr GmbH, a Germany-based data warehousing, data mining and personalization consultancy. "Combining the power of Clementine's graphical user interface with the scalability Oracle Data Mining creates a best-of-breed solution for data mining." Clementine 9.0 will enable analysts to use the Clementine interface to build, browse and score models in the Oracle Database 10g using techniques available with Oracle Data Mining. Oracle Data Mining algorithms, including Naive Bayes, Adaptive Bayes Network and Support Vector Machines, appear as nodes in the Clementine interface. These techniques can be used just like any other techniques that are native in Clementine. "Oracle Database 10g has been receiving high marks for its manageability, high efficiency and productivity," says Peter Caron, SPSS senior product manager. "Oracle Database 10g and Oracle Data Mining share with Clementine those same three qualities. To access, build and deploy models provided by Oracle 10g will enable analysts more manageability, higher efficiency and greater productivity."