Course Overview

Advanced Data Preparation Using IBM SPSS Modeler is a one day instructor-led classroom course that covers additional topics to aid in the preparation of data for a successful data mining project. You will learn how to partition records from files, handle missing data, modify fields and create new fields, and work with dates, strings and sequence data.

Who Should Attend

This advanced course is intended for anyone who wishes to become familiar with the full range of techniques available in IBM SPSS Modeler for data manipulation.

Course Certifications

This course is part of the following Certifications:

Prerequisites

  • General computer literacy.
  • Some experience using IBM SPSS Modeler including familiarity with the Modeler environment, creating streams, reading data files, and doing simple data exploration and manipulation.
Prior completion of Introduction to IBM SPSS Modeler and Data Mining is strongly encouraged.
  • Introduction to IBM SPSS Modeler and Data Mining (V14.2)
  • Introduction to IBM SPSS Modeler and Data Mining (V15)

Course Content

Data Understanding
  • Handling Missing
  • Handling Outliers
Dates and Strings
  • Importing Dates from Data Sources
  • Date Functions
  • String Functions
Data Transformations
  • Filling Fields
  • Binning Functions
  • Transforming Fields
Sequence Data
  • Sequence Functions
  • Count and State Forms of the Derive Node
  • Restructuring Sequence Data Using the Restructure Node
  • Restructuring Sequence Data Using the History Node
Sampling Data
  • Simple Sampling
  • Complex Sampling
  • Partitioning
Efficiency
  • Set Globals
  • SQL Optimization