IBM Planning Analytics v2.1.x: Design and Develop Models in PAW

• Describe TM1 server architecture and in-memory processing
• Create and access a TM1 server using Planning Analytics Workspace
• Create and edit dimensions using Planning Analytics Workspace
• Design cubes based on business requirements
• Explain TurboIntegrator process components
• Combine rules and dimension structures to perform calculations
• Create effective feeder statements
• Use DB functions to link cubes with different dimensionality
• Enable users to navigate to related detail data
• Implement advanced rule-based modeling techniques
• Design maintainable currency conversion models
• Implement models that support rolling forecasts

Analysts

Participants should have the following:

• A general understanding of business analytics or performance management concepts
• Basic familiarity with IBM Planning Analytics terminology
• Experience navigating web-based applications

Unit 1: Overview of IBM Planning Analytics

• Explain the role of IBM Planning Analytics in financial performance management
• Identify core Planning Analytics components and services
• Describe TM1 server architecture and in-memory processing
• Navigate the Planning Analytics Workspace modeling environment
• Create and access a TM1 server using Planning Analytics Workspace

Unit 2: Creating Dimensions in PAW

• Describe the role of dimensions and members in a Planning Analytics model
• Create and edit dimensions using Planning Analytics Workspace
• Import dimension structures from external files
• Use member attributes to enhance usability and reporting
• Explain how hierarchies support alternative rollups of data

Unit 3: Building Multidimensional Cubes

• Explain what cubes are and how they store data
• Design cubes based on business requirements
• Create cubes using existing dimensions
• Apply cube properties and attributes appropriately
• Implement pick lists to control data entry

Unit 4: Data Loading and Maintenance

• Identify supported data sources for Planning Analytics
• Explain TurboIntegrator process components
• Create and run processes to load cube and dimension data
• Maintain data accuracy using delete and accumulate techniques
• Schedule processes using chores

Unit 5: Building and Applying Business Rules

• Describe how rules are evaluated in Planning Analytics
• Write rules using area definitions and functions
• Apply rules at leaf and consolidated levels
• Use rules to share data between cubes
• Combine rules and dimension structures to perform calculations

Unit 6: Optimizing Rule Performance

• Explain how sparsity affects cube performance
• Use SKIPCHECK to optimize rule evaluation
• Create effective feeder statements
• Troubleshoot consolidation and feeder issues
• Trace rule-driven and consolidated values

Unit 7: Efficient Data Transfer and Transformation

• Use DB functions to link cubes with different dimensionality
• Describe TurboIntegrator scripting best practices
• Transfer and transform data between cubes
• Manage uneven hierarchies using processes 

Unit 8: Customizing Drill-Through Navigation

• Explain the Planning Analytics drill-through process
• Create drill processes using TurboIntegrator
• Associate drill processes with cube cells
• Enable users to navigate to related detail data 

Unit 9: Advanced Rule Modeling Techniques

• Describe virtual cubes and their use cases
• Use lookup cubes in calculations
• Apply relative proportional spreading
• Reference attributes within rules
• Implement advanced rule-based modeling techniques 

Unit 10: Designing Flexible Currency Conversion Models

• Explain common currency conversion requirements
• Use control cubes and lookup techniques
• Create rules to convert currencies
• Design maintainable currency conversion models 

Unit 11: Flexible Time Modeling Strategies

• Describe discrete and continuous time modeling approaches
• Select appropriate time structures based on requirements
• Implement models that support rolling forecasts
• Extend existing models for fiscal variations