Detailed Course Outline
1. Introduction to Decision Management • What is Decision Management? • Why Use Decision Management? • Analytical Decision Management • Five Steps of Decision Management • Use of Data • Historical and Operational Data • Classification Models • User Defined Rules • Deploying Models 2. A Sample Session: Managing Customer Interactions • Five Steps in Decision Management • Demonstration: A Marketing Call Center Business Case 3. Defining Data Sources • Data Structure • Field Storage • Field Measurement Level • Data Step • Project Data Source • Derived Tab • Secondary Data Sources • Compatibility of Data Sources 4. Defining Global Selections • Adding Rules to Global Selections • Defining and Sharing Rules • Evaluating Rules 5. Creating Rules from Models • Predictive Models • Predictive Rule Models • Clustering Models • Association Models • Automated Data Preparation & Partitioning • Evaluating Models 6. Defining Outcomes • Specify Project Duration • Include / Exclude Cases from Project • Define Action Categories • Create Allocation Rules 7. Prioritize, Optimize and Combine Outcomes • Selecting From Alternative Actions • Prioritizing Outcomes • Optimizing Outcomes • Combining Outcomes 8. Deploying Models for Scoring • Why Deploy the Project? • Real Time Scoring Panel • Batch Scoring Panel • Scoring Configurations • Using the Scoring View 9. Building a Custom Application • Application Configuration • Creating a New Application 10. Using Modeler Streams in ADM • Using Modeler Streams • Minimum Requirements for a Stream • Using a Stream in a Project