Technical IT

Introduction to IBM SPSS Modeler and Data Mining (v18)

Arrow ECS

Arrow ECS

Introduction

This IBM E-leaning course, equivalent to 2 days duration, provides an overview of data mining and the fundamentals of using IBM SPSS Modeler. The principles and practice of data mining are illustrated using the CRISP-DM methodology. The course structure follows the stages of a typical data mining project, from collecting data, to data exploration, data transformation, and modeling to effective interpretation of the results. The course provides training in the basics of how to read, prepare, and explore data with IBM SPSS Modeler, and introduces the student to modeling.

When enrolling in a Self Paced Virtual Classroom or Web Based
Training course, before you enroll, please review the Self-Paced Virtual Classes
and Web-Based Training Classes on our Terms and Conditions page, as well as the
system requirements, to ensure that your system meets the minimum requirements
for this course.
http://www.ibm.com/training/terms


Summary

Course Programme

1: Introduction to data mining

• List two applications of data mining
• Explain the stages of the CRISP-DM process model
• Describe successful data-mining projects and the reasons why projects fail
• Describe the skills needed for data mining

2: Working with IBM SPSS Modeler

• Describe the MODELER user-interface
• Work with nodes
• Run a stream or a part of a stream
• Open and save a stream
• Use the online Help

3: Creating a data-mining project

• Explain the basic framework of a data-mining project
• Build a model
• Deploy a model

4: Collecting initial data

• Explain the concepts "data structure", "unit of analysis", "field storage" and "field measurement level"
• Import Microsoft Excel files
• Import IBM SPSS Statistics files
• Import text files
• Import from databases
• Export data to various formats

5: Understanding the data

• Audit the data
• Explain how to check for invalid values
• Take action for invalid values
• Explain how to define blanks

6: Setting the unit of analysis

• Set the unit of analysis by removing duplicate records
• Set the unit of analysis by aggregating records
• Set the unit of analysis by expanding a categorical field into a series of flag fields

7: Integrating data

• Integrate data by appending records from multiple datasets
• Integrate data by merging fields from multiple datasets
• Sample records

8: Deriving and reclassifying fields

• Use the Control Language for Expression Manipulation (CLEM)
• Derive new fields
• Reclassify field values

9: Identifying relationships

• Examine the relationship between two categorical fields
• Examine the relationship between a categorical field and a continuous field
• Examine the relationship between two continuous fields

10: Introduction to modeling

• List three modeling objectives
• Use a classification model
• Use a segmentation model


Requirements


Anyone who wants to become familiar with IBM SPSS Modeler.

General computer literacy.

Overview

  • Location: Online
  • Telephone: 0333 443 2239
  • Residential: No
  • Course Title: Introduction to IBM SPSS Modeler and Data Mining (v18)
  • Duration: 0 Days
  • Cost: £480 (Ex VAT)
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