IBM Cognos 8 BI Framework Manager: Design Metadata Models (V8.4) SPVC

Overview of IBM Cognos 8 BI

• Discuss IBM Cognos 8 and Performance Management
• Describe IBM Cognos 8 BI components
• Describe IBM Cognos 8 architecture at a high level
• Define IBM Cognos 8 groups and roles
• Explain how to extend IBM Cognos 8

Identify Common Data Structures

• Examine the characteristics of operational databases and databases designed for reporting
• Examine relationships and cardinality
• Identify different data traps
• Examine OLAP data sources

Gather Requirements

• Examine key modeling recommendations
• Define reporting requirements
• Explore data sources to identify data access strategies

Create a Baseline Project

• Examine the IBM Cognos 8 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

Prepare Reusable Metadata

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

Model for Predictable Results: Identify Reporting Issues

• Describe multi-fact queries and when full outer joins are appropriate
• Describe how IBM Cognos 8 uses cardinality
• Identify reporting traps
• Use tools to analyze the model

Model for Predictable Results: Virtual Star Schemas

• Identify the advantages of modeling metadata as a star schema
• Model in layers
• Create aliases to avoid ambiguous joins
• Merge query subjects to create as view behavior

Model for Predictable Results: Consolidate Metadata

• Create virtual facts to simplify writing queries
• 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

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

Implement 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

Specify Determinants

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

Create 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