IBM Planning Analytics: Design and Develop Models in Performance Modeler (v2.0) SPVC

1: Overview of IBM Planning Analytics • review financial performance management • identify the Planning Analytics position in a performance management system • describe the IBM Planning Analytics components and architecture • explore IBM Planning Analytics applications • explore the IBM Planning Analytics environment • manage and organize a model 2: Create and customize dimensions • review cubes, dimensions, and elements • create dimensions manually • import dimensions • edit dimensions • create dimension calculations • use Guided Import to create a dimension 3: Create and customize cubes • construct a new cube • discuss cube properties • edit a cube structure • review and use a pick list • create cube calculations 4: Import data • identify data sources • create processes to load data • create a process to delete data in a cube • create processes to update and maintain the model 5: Share data across cubes with links • discuss and list types of links • create and modify links • review rule- and process-based links 6: Complete the income statement model • discuss the model development process • complete objects for the model • review tools to aid in model development 7: Create applications • explain the application types • access an IBM Planning Analytics application • create a new application • set the available clients • apply security in the application • activate and de-activate an application 8: Additional modeling techniques • create dynamic subsets • use dimension functions • implement business logic • improve cube performance • use Planning Analytics utilities 9: Convert currencies • discuss currency challenges • review control cubes • create rules for currency conversion • use Planning Analytics techniques to reduce maintenance 10: Model data with Architect • describe IBM Planning Analytics Architect • record MDX queries • customize drill-through paths 11: Model for different fiscal requirements • discuss time considerations • use discrete time dimensions • implement a continuous time dimension model Additional Exercise (Optional) Optimize and tune models (Optional) Customize business rules (Optional) Optimize rule performance (Optional)