Training offering

IBM SPSS Data Collection Scripting (Intermediate Data Management)

Overview

This course builds on the knowledge acquired during the 'Introduction to Data Management' course and provides more complex functionality within each of the Data Management steps. You will build on their scripting knowledge and tackle more intricate scenarios.The survey and case data used during this course are the solutions to the IBM SPSS Data Collection Scripting (Survey Creation) Level I course, thereby providing a sense of continuity to students from both classes. Additionally, the solution created during the 'Introduction To Data Management' course will be used to drive the student exercises.

Public

This course is for scriptwriters who will be responsible for the data management of projects. In order words, taking initial datasets and surveys files and modifying the records appropriately.

Prerequisits

You should have taken the 'IBM SPSS Data Collection Scripting (Intro to Data Management)' course as the content builds on specific knowledge gained during that course.

Objective

Please refer to course overview for description information.

Topics

Lesson 1: Course Introduction

Lesson 2: Survey files and data

• Explain how hierarchical survey content is stored and referenced
• Modify data

Lesson 3: The Data Management process

• Create references to external files
• Build global text substitutions
• Explain the concept and process of Weighting

Lesson 4: Options for reading data in and out

• Explain how to 'modify' data record selection
• Explain the customized connection property option

Lesson 5: Adding derived survey variables

• Demonstrate building a 'dynamically' derived variable
• Explain how to create our weighting variable

Lesson 6: Actions prior to opening input data

• Explain how to script against the survey metadata file

Lesson 7: Actions after reading Input data

• Explain how to use the WScript.Shell object
• Explain how to use the VBScript.RegExp object

Lesson 8: Using subroutines and functions

• Explain and create subroutines
• Explain and create functions

Lesson 9: Looping through records

• List additional best practices associated with modifying records
• Describe more involved cleaning solutions

Lesson 10: Error Handling

• Explain the error object and the different ways of handling errors

Lesson 11: Actions prior to closing output data

• Define and explain the weighted solutions available

Lesson 12: Actions after data output closed

• Deploy automation at the end of the solution