Data Understanding in IBM SPSS Modeler

IBM SPSS Modeler is an extensive predictive analytics platform designed to bring predictive intelligence to decisions made by individuals, groups, systems, and the enterprise. IBM SPSS Modeler has an easy-to-use drag-and-drop user interface with a complete set of tools for accessing data, data examination, preparation, modelling, evaluation, and deployment.  

IBM SPSS Modeler users have a complete toolset to build predictive models from start to finish. Modeler uses node-based, visual programming. Users pick nodes from palettes and place them on the stream canvas. Once nodes have been placed on the stream canvas and edited, they can be linked to form a stream. A stream represents a flow of data through several operations (nodes) to a destination that can be in the form of output (either text or chart), a model, or the export of data to another format (e.g., a database).  

The SPSS team at Version 1 provides extensive Modeler training, offering both express and longer courses. Training can also be customised for individual users and groups.  

The data understanding and data preparation phase of any data science project is time-consuming and, at times, confusing. This two-hour express course covers data auditing options and data understanding in IBM SPSS Modeler and is designed to make data examination, exploration and auditing easy and transparent.

This course will cover the following topics:

• Review of CRISP-DM
• Review of the data understanding phase
• Using the Data Audit node
• Data Audit node output
• Types of missing data and tools to assess missing data
• Tools to assess data quality
• Examining and handling outliers and anomalous data
• Using the View Data option

Course attendees will receive sample data files and step-by-step exercises that can be completed following the course.

Best for: Anyone who wants to focus on data understanding in IBM SPSS Modeler.