Description
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Course details
| IBM course code: P8361G | Category: IBM Planning Analytics / IBM Planning Analytics |
| Delivery: Online & on-site** | Course length in days: 5 |
Target audience
Modelers
Desired Prerequisites:
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/
Instructors
The great majority of the IBM courses we offer are taught directly by our engineers. This is the only way we can guarantee the highest quality. We complement all the training with our own materials and laboratories, based on our experience during the deployments, migrations and courses that we have carried out during all these years.
Added value
Our courses are deeply role oriented. To give an example, the needs for technology mastery are different for developer teams and for the people in charge of deploying and managing the underlying infrastructure. The level of previous experience is also important and we take it very seriously. That is why beyond (boring) commands and tasks, we focus on solving the problems that arise in the day to day of each team. Providing them with the knowledge, competencies and skills required for each project. In addition, our documentation is based on the latest version of each product.
Agenda and course syllabus
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
Do you need to adapt this syllabus to your needs? Are you interested in other courses? Ask us without obligation.
Locations for on-site delivery
- Austria: Vienna
- Belgium: Brussels, Ghent
- Denmark: Cophenhagen
- Estonia: Tallinn
- Finland: Helsinki
- France: Paris, Marseille, Lyon
- Germany: Berlin, Munich, Cologne, Hamburg
- Greece: Athens, Thessaloniki
- Italy: Rome
- Louxemburg: Louxembourg (city)
- Netherlands: Amsterdam
- Norway: Oslo
- Portugal: Lisbon, Braga, Porto, Coimbra
- Slovakia: Bratislava
- Slovenia: Bratislava
- Spain: Madrid, Sevilla, Valencia, Barcelona, Bilbao, Málaga
- Sweden: Stockholm
- Turkey: Ankara
- United Kingdom: London
