IBM Cognos Framework Manager: Design Metadata Models (v11.0) SPVC

1. Introduction to IBM Cognos Analytics • Describe IBM Cognos Analytics and its position within an analytics solution • Describe IBM Cognos Analytics components • Describe IBM Cognos Analytics at a high level • Explain how to extend IBM Cognos 2. Identifying common data structures • Define the role of a metadata model in Cognos Analytics • Distinguish the characteristics of common data structures • Understand the relative merits of each model type • Examine relationships and cardinality • Identify different data traps • Identify data access strategies 3. Defining requirements • Examine key modeling recommendations • Define reporting requirements • Explore data sources to identify data access strategies • Identify the advantages of modeling metadata as a star schema • Model in layers 4. Creating a baseline project • Follow the IBM Cognos and Framework Manager workflow processes • Define a project and its structure • Describe the Framework Manager environment • Create a baseline project • Enhance the model with additional metadata 5. Preparing reusable metadata • Verify relationships and query item properties • Create efficient filters by configuring prompt properties 6. Modeling for predictable results: Identifying reporting Issues • Describe multi-fact queries and when full outer joins are appropriate • Describe how IBM Cognos uses cardinality • Identify reporting traps • Use tools to analyze the model 7: Modeling for predictable results: Virtual star schemas • Understand the benefits of using model query subjects • Use aliases to avoid ambiguous joins • Merge query subjects to create as view behavior • Resolve a recursive relationship • Create a complex relationship expression 8. Modeling for predictable results: consolidate metadata • Create virtual dimensions to resolve fact-to-fact joins • Create a consolidated modeling layer for presentation purposes • Consolidate snowflake dimensions with model query subjects • Simplify facts by hiding unnecessary codes 9. Creating calculations and filters • Use calculations to create commonly-needed query items for authors • Use static filters to reduce the data returned • Use macros and parameters in calculations and filters to dynamically control the data returned 10. Implementing a time dimension • Make time-based queries simple to author by implementing a time dimension • Resolve confusion caused by multiple relationships between a time dimension and another table 11. Specifying determinants • Use determinants to specify multiple levels of granularity and prevent double-counting 12. Creating the presentation view • Identify the dimensions associated with a fact table • Identify conformed vs. non-conformed dimensions • Create star schema groupings to provide authors with logical groupings of query subjects • Rapidly create a model using the Model Design Accelerator • Rapidly create a model using the Model Design Accelerator 13. Working with different query subject types • Identify the effects of modifying query subjects on generated SQL • Specify two types of stored procedure query subjects • Use prompt values to accept user input 14. Setting Security in Framework Manager • Examine the IBM Cognos security environment • Restrict access to packages • Create and apply security filters • Restrict access to objects in the model 15. Creating Analysis objects • Apply dimensional information to relational metadata to enable OLAP-style queries • Sort members for presentation and predictability • Define members and member unique names • Identify changes that impact a MUN 16. Managing OLAP Data Sources • Connect to an OLAP data source (cube) in a Framework Manager project • Publish an OLAP model • Publish a model with multiple OLAP data sources • Publish a model with an OLAP data source and a relational data source 17. Advanced generated SQL concepts and complex queries • Governors that affect SQL generation • Stitch query SQL • Conformed and non-conformed dimensions in generated SQL • Multi-fact/multi-grain stitch query SQL • Variances in IBM Cognos Analytics - Reporting generated SQL • Dimensionally modeled relational SQL generation • Cross join SQL • Various results sets for multi-fact queries 18. Using advanced parameterization techniques in Framework Manger • Identify environment and model session parameters • Leverage session, model, and custom parameters • Create prompt macros • Leverage macro functions associated with security 19. Model maintenance and extensibility • Perform basic maintenance and management on a model • Remap metadata to another source • Import and link a second data source • Run scripts to automate or update a model • Create a model report 20. Optimizing and tuning Framework Manager models • Identify how minimized SQL affects model performance • Use governors to set limits on query execution • Identify the impact of rollup processing on aggregation • Apply design mode filters • Limit the number of data source connections • Use the quality of service indicator 21. Working in a Multi-Modeler Environment • Segment and link a project • Branch a project and merge results 22. Managing packages in Framework Manager • Specify package languages and function sets • Control model versioning • Nest packages Appendix A. Additional modeling techniques • Leverage a user defined function • Identify the purpose of query sets • Use source control to manage Framework Manager files Appendix B. Modeling multilingual metadata • Customize metadata for a multilingual audience