IBM SPSS Modeler Foundations V18.2 0A069G

• Data scientists
• Business analysts
• Clients who are new to IBM SPSS Modeler or want to find out more about using it

Introduction to IBM SPSS Modeler

• Introduction to data science

• Describe the CRISP-DM methodology

Build models and apply them to new data

Collect initial data

• Describe field storage

• Describe field measurement level

• Import from various data formats

Export to various data formats

Understand the data

• Audit the data

• Check for invalid values

• Take action for invalid values

Define blanks

Set the unit of analysis

• Remove duplicates

• Aggregate data

• Transform nominal fields into flags

Restructure data

Integrate data

• Append datasets

• Merge datasets

Sample records

Transform fields

• Use the Control Language for Expression Manipulation

• Derive fields

• Reclassify fields

Bin fields

Further field transformations

• Use functions

• Replace field values

Transform distributions

Examine relationships

• Examine the relationship between two categorical fields

• Examine the relationship between a categorical and continuous field

Examine the relationship between two continuous fields

Introduction to modeling

• Describe modeling objectives

• Create supervised models

Create segmentation models

Improve efficiency

• Use database scalability by SQL pushback

• Process outliers and missing values with the Data Audit node

• Use the Set Globals node

• Use parameters

Use looping and conditional execution

• Knowledge of your business requirements

Introduction to IBM SPSS Modeler

• Introduction to data science

• Describe the CRISP-DM methodology

Build models and apply them to new data

Collect initial data

• Describe field storage

• Describe field measurement level

• Import from various data formats

Export to various data formats

Understand the data

• Audit the data

• Check for invalid values

• Take action for invalid values

Define blanks

Set the unit of analysis

• Remove duplicates

• Aggregate data

• Transform nominal fields into flags

Restructure data

Integrate data

• Append datasets

• Merge datasets

Sample records

Transform fields

• Use the Control Language for Expression Manipulation

• Derive fields

• Reclassify fields

Bin fields

Further field transformations

• Use functions

• Replace field values

Transform distributions

Examine relationships

• Examine the relationship between two categorical fields

• Examine the relationship between a categorical and continuous field

Examine the relationship between two continuous fields

Introduction to modeling

• Describe modeling objectives

• Create supervised models

Create segmentation models

Improve efficiency

• Use database scalability by SQL pushback

• Process outliers and missing values with the Data Audit node

• Use the Set Globals node

• Use parameters

Use looping and conditional execution