IBM Cognos Framework Manager

CloudLabs

Projects

Assignment

24x7 Support

Lifetime Access

.

Course Overview

IBM Cognos Framework Manager is a metadata modeling tool that drives query generation for IBM Cognos software. A model is a collection of metadata that includes physical information and business information for one or more data sources. IBM Cognos software enables performance management on normalized and denormalized relational data sources and a variety of OLAP data sources.

At the end of the training, participants will be able to:

Pre-requisite

  1. Knowledge of common industry standard data structures and design
  2. Experience with SQL
  3. Experience gathering requirements and analyzing data

Duarion

5 days

Course Outline

  • Discuss IBM Cognos and Performance Management
  • Describe IBM Cognos components
  • Describe IBM Cognos architecture at a high level
  • Define IBM Cognos groups and roles
  • Explain how to extend IBM Cognos
  • Examine the characteristics of operational databases and databases designed for reporting
  • Examine relationships and cardinality
  • Identify different data traps
  • Examine dimensional data sources
  • Examine key modeling recommendations
  • Define reporting requirements
  • Explore data sources to identify data access strategies
  • Examine the IBM Cognos BI 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
  • Identify facts and dimensions
  • Examine relationships, and data traps
  • 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 BI uses cardinality
  • Identify reporting traps
  • Use tools to analyze the model
  • 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
  • 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
  • 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
  •  
  • Use determinants to specify multiple levels of granularity and prevent double-counting
  • 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
  • Work with Different Query Subject Types
  • Identify key differences and recommendations for using data source, model, and stored procedure query subjects
  • Identify the effects on generated SQL when modifying query subjects, SQL settings and relationships
  • Examine the IBM Cognos BI security environment
  • Restrict access to packages
  • Create and apply security filters
  • Restrict access to objects in the model
  • Apply dimensional information to relational Metadata to enable OLAP-style queries
  • Define members and member unique names
  • Identify changes that impact a MUN
  • Sort members for presentation and predictability
  • 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
  • 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 Report Studio generated SQL
  • Dimensionally modeled relational SQL generation
  • Cross join SQL
  • Various results sets for multi-fact queries
  • Identify environment and model session parameters
  • Leverage session, model, and custom parameters
  • Create prompt macros
  • Leverage macro functions associated with security
  • 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
  • Identify and implement techniques to optimize and tune your Framework Manager models
  • Use Dynamic Query Mode in Framework Manager
  • Work in a Multi-Modeler Environment
  • Segment and link a project
  • Branch a project and merge results
  • Specify package languages and function sets
  • Control model versioning
  • Nest packages
  • Leverage a user defined function
  • Set the order of operations in a model calculation
  • Externalize query subjects
  • Prepare IBM Cognos 10 content for use as a data source in Transformer
  • Create query sets
  • Use external source control through Windows Explorer
  • Customize metadata for a multilingual audience

Reviews