Course Overview
Course Duration 1 day.
Advanced Data Preparation Using IBM SPSS Modeler (V16) – covers advanced topics to aid in the preparation of data for a successful data mining project. You will learn how to use functions, deal with missing values, use advanced field operations, handle sequence data, apply advanced sampling methods, and improve efficiency.

Who Should Attend
This course is for IBM SPSS Modeler Analysts and IBM SPSS Modeler Data Experts who want 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
You should have:
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 using derive node.

Course Objectives
Use date functions
Use conversion functions
Use string functions
Use statistical functions
Use missing value functions

Course Content
1. Using Functions
Use date functions
Use conversion functions
Use string functions
Use statistical functions
Use missing value functions
2. Data Transformations
Use the Filler node to replace values
Use the Binning node to recode continous fields
Use the Transform node to change a field’s distribution
3. Working with Sequence Data
Use cross-record functions
Use the count mode in Derive node
Use the Restructure node to expand a continous field into a series of continous fields
Use the Space Time Boxes node to work with geospatial and time data
4. Sampling Records
Use the Sample node to draw simple and complex samples
Draw complex samples
Partition the data into a training and a testing set
Reduce or boost the number of records
5. Improving Efficiency
Use database scalability by SQL pushback
Use the Data Audit node to process outliers and missing values
Use the Set Globals node
Use parameters
Use looping and conditional execution