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> > > P8352G Detaillierte Beschreibung

IBM Planning Analytics: Design and Develop Models in Performance Modeler (v2.0) (P8352G)

Detaillierter Kursinhalt

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 model2: 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 dimension3: Create and customize cubes• construct a new cube• discuss cube properties• edit a cube structure• review and use a pick list• create cube calculations4: 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 model5: Share data across cubes with links• discuss and list types of links• create and modify links• review rule- and process-based links6: Complete the income statement model• discuss the model development process• complete objects for the model• review tools to aid in model development7: 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 application8: Additional modeling techniques• create dynamic subsets• use dimension functions• implement business logic• improve cube performance• use Planning Analytics utilities9: Convert currencies• discuss currency challenges• review control cubes• create rules for currency conversion• use Planning Analytics techniques to reduce maintenance10: Model data with Architect• describe IBM Planning Analytics Architect• record MDX queries• customize drill-through paths11: Model for different fiscal requirements• discuss time considerations• use discrete time dimensions• implement a continuous time dimension modelAdditional Exercise (Optional)Optimize and tune models (Optional)Customize business rules (Optional)Optimize rule performance (Optional)

 
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