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Extending versatility of python to nonprogrammer

IBM SPSS Programmability

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Extending versatility of python to nonprogrammer

  1. 1. Extending versatility of Python to nonprogrammer by Armand Ruiz (IBM SPSS Product Manager) 1st Annual Conference on Python applications in Data Analysis, Machine Learning, and Web
  2. 2. About Me • Role: IBM SPSS Product Manager Programmability • E-mail: • Twitter: @armand_ruiz • Website:
  3. 3. Content available here:
  4. 4. IBM SPSS Software: IBM SPSS Modeler – Latest version is 17 IBM SPSS Statistics – Latest version is 23 Trials available
  5. 5. Extensibility with R/Python for Modeler AND Statistics • Build and score R/Python models through the Modeler and Statistics GUIs • Use R/Python functions for data preparation • Generate R/Python Charts and Outputs within SPSS output management system • Custom Dialog Builder:
  6. 6. Enterprise R/Python Scalability and Deployment • A range of options exist for scaling R execution via Modeler. The following modes of operation are supported: - Modeler Desktop - Modeler Server (Python/R execution on Server Tier to minimise data movement) - Pushdown to Analytic Server (Hadoop) leveraging Map Reduce (HUGE!!!) - Database pushback through leveraging Netezza, SAP Hana or Oracle R engines • Streams can be deployed/automated through: - Modeler Batch - C&DS Job Scheduling and Model Management - C&DS Scoring Service/Solution Publisher/InfoSphere Streams - IBM SPSS Analytical Decision Management
  7. 7. IBM SPSS Nodes
  8. 8. 9
  9. 9. 11
  10. 10. Social Databases Models And many more…! IBM Predictive Extensions Geospatial
  11. 11. New IBM SPSS Community
  12. 12. Q&A • E-mail: • Twitter: @armand_ruiz • Website: