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Visit the Predictive Analytics Resource Site

If you missed a session or want to share your knowledge with colleagues, the Predictive Analytics Resource Site is your one-stop resource for all things predictive analytics. Download white papers, gain access to session presentations, and view real-life videos of how predictive analytics helps transform organizations like yours.

Hands-on Lab Sessions

This is a unique opportunity for you to get intensive, classroom-quality training by our highly experienced professional instructors. Choose from several different three-hour sessions that cover a wide range of IBM SPSS products. Each session lets you explore and interact directly with live software through well-proven, hands-on training exercises and workshops. All hands-on labs listed below are included in your conference registration.

This session will introduce a range of topics in data mining and give participants of all proficiency levels hands-on experience using IBM SPSS Modeler software. Attendees will receive an overview of the products data mining capability and then complete self-paced exercises for several of the most common data mining tasks, including integration with IBM SPSS Statistics. Participants will have the opportunity to work with text analytics and see how unstructured data can be used with structured data to build more accurate models. Finally, participants will be able to see and explore the power and capabilities of the IBM SPSS Collaboration and Deployment Services platform for automation and security of data mining resources.

This session will provide an instructor-guided, hands-on experience using IBM SPSS Statistics to find patterns and test ideas on real data. Beginners will learn how to use simple descriptive statistics, graphical methods, cross tabulation and regression analysis to explore a data set of current interest. Advanced IBM SPSS Statistics users will also have the option to learn about extension commands, which can extend or modify the built-in capabilities through the use of the Python or R languages and without having to learn new technology.