P8361G – IBM Planning Analytics: Design and Develop Models in Architect (v2.0)

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This course is designed to teach modelers how to build a complete model in IBM Planning Analytics using the Architect tool. Through a series of lectures and hands-on exercises, students will learn how to set up and verify dimensions, cubes, and views, manually enter data into these structures, and define the data that users can see. Students will also learn how to transfer data into the TM1 model, including the use of TurboIntegrator scripts to perform data transfer. In addition, the course outlines how to customize drill paths, convert currencies, model for different fiscal requirements, and deploy IBM Planning Analytics applications to the web.

Course Length: 5 day(s)

Course Price: $3925 CAD

Available Course Formats:

  • In-class
  • Instructor Led Online
  • Self-Paced Virtual Classroom

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Course: P8361G – IBM Planning Analytics: Design and Develop Models in Architect (v2.0)

Course Outline:

  1. Overview of IBM Planning Analytics
    - Review financial performance management
    - Identify the IBM Planning Analytics position in a performance management system
    - Describe the IBM Planning Analytics components and architecture
    - Describe TM1 server fundamentals
    - Describe fundamental modeling concepts
  2. Create dimensions
    - Describe cubes and dimensions
    - Create dimensions manually
    - Edit dimensions
    - Create dimensions using TurboIntegrator
  3. Build cubes and views
    - Describe cubes and data points
    - Create cubes
    - Construct views of data in cubes
    - Create and use a pick list
  4. Load and maintain data
    - Identify data sources
    - Create processes to load data
    - Create processes to delete data in a cube
    - Create processes to update and maintain the model
  5. Add business rules
    - Describe a rule
    - Construct rules for elements or consolidations
    - Use functions in rules
    - Optimize rule performance
    - Describe rules in a rule worksheet
  6. Optimize rule performance
    - Describe consolidations and sparsity
    - Enhance consolidation performance using SKIPCHECK
    - Use FEEDERS to optimize aggregations
    - Check the accuracy of rules and feeders
  7. Transfer data into the model
    - Describe the Advanced tabs in TurboIntegrator
    - Load custom data into a cube
    - Add a subset to a dimension
    - Use logic in scripts
    - Export data to ASCII
    - Move data between versions
    - Construct chores
  8. Customize drill paths
    - View related data
    - Create a drill process
    - Create a drill assignment rule
    - Edit a drill process
  9. Using rules for advanced modeling
    - Describe virtual cubes
    - List uses for lookup cubes
    - Create and use a spread profiles cube
    - Implement moving balances in a cube
  10. Convert currencies
    - Describe currency challenges
    - Create a currency dimension
    - Create a currency cube
    - Create rules for currency conversion
  11. Model for different fiscal requirements
    - Identify time considerations
    - Use discrete time dimensions
    - Implement a continuous time dimension model
  12. Deploy IBM Planning Analytics 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 deactivate an application
  • Appendix A: Optimize and tune models
    - Identify characteristics of large models
    - Describe strategies to improve model performance
  • Appendix B: Identify common data structures
    - Identify characteristics of operational and reporting databases
    - Discuss Online Analytical Processing (OLAP)
    - Examine core model design principles
    - Identify the basic tasks required to create an IBM Planning Analytics model and deploy it


This advanced course is intended for Modelers.


  • Understanding of the metrics and drivers of your business
  • Significant experience with Microsoft Excel spreadsheets (functions, macros, etc.)
  • Basic knowledge of OLAP and IBM Planning Analytics

To gain this knowledge, visit the following websites:

  • IBM Planning Analytics Learning Center at https://developer.ibm.com/clouddataservices/docs/ibm-planning-analytics/how-to
  • IBM Planning Analytics YouTube Channel at https://www.youtube.com/channel/UCGYcFhVXoA29v8kSbspLudA/featured
  • IBM Planning Analytics Community at https://www.ibm.com/communities/analytics/planning-analytics/

Instructor Led In Classroom

Newcomp can directly deliver  IBM Business Analytics courses for Business Intelligence, Performance Management, and IBM Advanced Analytics through the use of in-class training facilities.

Currently,  in-class courses are offered in Markham, Ottawa, Vancouver, Halifax, and Edmonton. Please note that classes can be added to new areas based on demand.

Instructor Led Online

Students receive the same quality as an in-class course, with a live instructor and the ability to participate in hands-on labs through real-life examples

ILOs help cut costs by reducing time and travel as they can be taken from home or the office and require only the use of a computer, high-speed wired internet and a headset.

Self Paced

Students can receive the same high-quality training, with the same courseware at their own speed and schedule with SPVC.  Individuals with busy schedules can complete a course over a 30-day timeframe at a lower price than in-class or ILO courses. Please note that there is no live interaction with an instructor in this format.


This course is available on-demand: request a specific course, location, time frame and/or format by completing this form. This offering increases schedule flexibility and allows us to accommodate people with different availabilities.

Customized Courses

On-site courses can also be customized based on user roles and needs within your organization. This option allows lower costs in travel and time and increased flexibility in scheduling. This format also enables students to work with the organization's data - adding value to the learning experience. This makes the training relevant and applicable to the students; daily tasks and therefore, results in a quicker path to productivity.