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

Description

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

Aim

Mit diesem umfangreichen Training on Demand erhalten Sie umfangreiches Wissen für das Designen von Meta Daten Modellen.

Participant requirements

You should have:

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

Recommended

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

Minimum Requirements (for PC) to use SPVC

• Windows 2000, XP, Vista, and 7
• Firefox, including v3.6.6
• Internet Explorer, including v8
• browser settings include:
  
  • Java Runtime Environment must be installed and enabled in the web browser
  • Web browser must be set to enable/allow JavaScript
  • Web browser Pop-up blocking mechanisms must be set to allow pop-ups from elearn.ihost.com
  • Cookies must be enabled
  • Flash-enabled
  • ActiveX-enabled

• CITRIX, for the remote lab (instructions to install included with the SPVC)

Participant

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