Duration

1 day

Course Description

In this course, you'll examine additional topics to aid in the preparation of data for a successful data mining project. You'll learn how to partition records from files, handle missing data, modify fields and create new fields, and work with dates, strings and sequence data.

Audience

This follow-up course to Introduction to IBM SPSS Modeler and Data Mining is designed for anyone who wishes to become familiar with the full range of techniques available in IBM SPSS Modeler for data and file manipulation.

Prerequisites

You should have:

General computer literacy.
Some experience using IBM SPSS Modeler (formerly Clementine) including familiarity with the IBM SPSS 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.

At Course Completion

Please refer to course overview for description information.

Course Outline

Sampling Data
Working with Dates
Data transformations on continuous fields
Working with string data
Working with sequence data
Writing out data files
Efficiency in IBM SPSS Modeler
Database Joins with IBM SPSS Modeler
Statistics transform node

Programme scope, delivery arrangements and suitability are confirmed during enquiry.