ESSENTIALS FOR IBM COGNOS ANALYTICS (V11.0) Training

Chapter 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 Analytics

Chapter 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

Chapter 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

Chapter 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

Chapter 5. Preparing reusable metadata

• Verify relationships and query item properties
• Create efficient filters by configuring prompt properties

Chapter 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

Chapter 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

Chapter 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

Chapter 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

Chapter 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

Chapter 11: Specifying determinants

• Use determinants to specify multiple levels of granularity and prevent double-counting

Chapter 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

Chapter 13. 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

Chapter 14. Introduction to IBM Cognos Analytics - Reporting

• Examine IBM Cognos Analytics - Reporting and its interface
• Explore different report types
• Create reports in preview or design mode
• Create a simple, sorted, and formatted report
• Examine dimensionally modelled and dimensional data sources
• Explore how data items are added queries
• Examine personal data sources and data modules

Chapter 15. Creating list reports

• Group, format, and sort list reports
• Describe options for aggregating data
• Create a multi-fact query
• Create a report with repeated data

Chapter 16. Focusing reports using filters

• Create filters to narrow the focus of reports
• Examine detail filters and summary filters
• Determine when to apply filters on aggregate data

Chapter 17. Creating crosstab reports

• Format and sort crosstab reports
• Create complex crosstabs using drag and drop functionality
• Create crosstabs using unrelated data items

Chapter 18. Present data graphically

• Create charts containing peer and nested columns
• Present data using different chart type options
• Add context to charts
• Create and reuse custom chart palettes
• Introduce visualization
• Present key data in a single dashboard report

Chapter 19. Focusing Reports Using Prompts

• Identify various prompt types
• Use parameters and prompts to focus data
• Search for prompt types
• Navigate between pages