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IBM Cognos Framework Manager: Design Metadata Models (V10.1) - ILO

Vendor:: IBM Corporation
Course:: I5152
Start Date:: Monday, June 25, 2012
Length:: 5 Days
Location:: Virtual Eastern, VR
Tuition:: $3,500

June

25

Virtual Eastern, VR

Course Description

IBM Cognos Education is now pleased to offer you our courses in an exciting new learning format, Instructor-led Online (ILO). Students are offered a similar experience to live classroom training, with the convenience of having it delivered directly to their desktop.

IBM Cognos Framework Manager: Design Metadata Models (V10.1) ?is a five-day, instructor-led course that provides participants with introductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing of metadata to the Web, enabling end users to easily author reports and analyze data.

Skills Gained

Overview of IBM Cognos

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

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 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

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 BI 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

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

Set Security in Framework Manager

Examine the IBM Cognos BI security environment
Restrict access to packages
Create and apply security filters
Restrict access to objects in the model

Create Analysis Objects

Apply dimensional information to relational Metadata to enable OLAP-style queries
Sort members for presentation and predictability

Manage MUNs in Framework Manager

Describe model types and data entities
Define members and member unique names
Identify changes that impact a MUN

Model for Drill Through in Framework Manager

Identify conformed values between data sources
Define a report drill through
Define a package-based drill through
Identify drill-through values

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 Report Studio generated SQL
Dimensionally modeled relational SQL generation
Cross join SQL
Various results sets for multi-fact queries

Use Advanced Parameterization Techniques in Framework Manger

Identify session and model parameters
Leverage session, model, and custom parameters
Create prompt macros
Leverage macro functions associated with security

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
View lineage
Create a model report

Optimize and Tune Framework Manager Models

Identify and implement techniques to optimize and tune your Framework Manager models

Work in a Multi-Modeler Environment

Implement repository control
Segment and link a project
Branch a project and merge results

Manage 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

Manage Framework Manager Packages

Specify package languages and function sets
Control model versioning
Nest packages

Who Can Benefit

This advanced course is for developers who design metadata models for use in IBM Cognos.

Prerequisites

Required:

Knowledge of common industry standard data structures and design
Experience with SQL
Experience gathering requirements and analyzing data

Recommended:

IBM Cognos Report Studio: Author Professional Reports Fundamentals (V10.1) or CBT equivalent

Syllabus

1. Overview of IBM Cognos

IBM Cognos and Performance Management
IBM Cognos components
IBM Cognos architecture at a high level
IBM Cognos groups and roles
Extend IBM Cognos

2. Identify Common Data Structures

Characteristics of operational databases and databases designed for reporting
Relationships and cardinality
Data traps
OLAP data sources

3. Gather Requirements

Key modeling recommendations
Define reporting requirements
Explore data sources to identify data access strategies

4. Create a Baseline Project

IBM Cognos BI and Framework Manager workflow processes
Define a project and its structure
Framework Manager environment
Create a baseline project
Enhance the model with additional metadata

5. Prepare Reusable Metadata

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

6. Model for Predictable Results: Identify Reporting Issues

Multi-fact queries and when full outer joins are appropriate
How IBM Cognos BI uses cardinality
Reporting traps
Use tools to analyze the model

7. Model for Predictable Results: Virtual Star Schemas

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

8. 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

9. 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. 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

11. Specify Determinants

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

12. Create the Presentation View

Dimensions associated with a fact table
Conformed vs. non-conformed dimensions
Create star schema groupings to provide authors with logical groupings of query subjects

13. Work with Different Query Subject Types

Key differences and recommendations for using data source, model, and stored procedure query subjects
Effects on generated SQL when modifying query subjects, SQL settings, and relationships