Model for Predictable Results in IBM Cognos Framework Manager – eLearning – k01011gwpl
Duration: 7.2 Hours
This offering teaches IBM Cognos Framework Manager data modelers how to model for predictable results. Participants will learn how to identify query and reporting issues, model virtual star schemas, and work with query subjects and relationships. They will learn how to consolidate metadata, use filters and calculations, and work with time dimensions.
Note: Guided eLearning is a self-paced offering which includes web-based content for self-study and videos (including audio) that demonstrate activities.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course. http://www.ibm.com/training/terms
Please refer to course overview
• Knowledge of OLAP concepts
• Knowledge of how to identify common data structures, define reporting requirements, and identify data access strategies
• Familiarity with the IBM Cognos Framework Manager user interface and workflow process
• Knowledge of how to create a baseline project
You will have the prerequisite knowledge if you have taken the K01010 Introduction to IBM Cognos Framework Manager course and understood the concepts presented there.
Model for Predictable Results in IBM Cognos Framework Manager
• Identify query issues
• Identify reporting traps: two facts with no dimension context
• Identify various other reporting traps
• Model virtual star schemas
• Use query subjects
• Modify relationships
• Consolidate metadata using virtual objects
• Create calculations
• Filter data
• Customize metadata for runtime
• Implement a time dimension
• Specify determinants