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This course is intended for core project team members wishing to acquire a broad understanding of a business intelligence (BI) platform implementation. You will perform hands-on demos and workshops that cover three essential topic areas: modeling, report authoring, and administration of a BI platform. Throughout the course, you will be guided to more-in depth training offerings and paths leading to certification.

eLearning

  • IBM Cognos for Microsoft Office: Integrate with Microsoft Office (v10.1/10.2) (B5130G)
  • IBM Cognos BI Event Studio: Create and Manage Agents (v8.4/10.1) (B5131G)
  • IBM Cognos Transformer: Create PowerCubes (v10.1) - recording (B5169G)
  • IBM Cognos Workspace Advanced: Introduction (v10.2.2) (B5A83G)
  • IBM Cognos Workspace Advanced: Intermediate (v10.2.2) (B5A84G)
  • IBM Cognos BI for Consumers (v10.2.2) (B5A88G)
  • IBM Cognos Workspace: Create Workspaces (v10.2.2) (B5A17G)

Note: While class exercises are performed within a Cognos v10.2.2 environment, our expert instructors can provide guidance on all versions and their differences.



Highlights:
  • Overview of IBM Cognos BI
  • Common data structures
  • Modeling requirements
  • Creating a baseline project
  • Reusable metadata
  • Identifying reporting issues
  • Model query subjects
  • Model for predictable results
  • Calculations and filters
  • Time dimensions
  • Specifying determinants
  • Creating the presentation view
  • Creating analysis objects
  • Introduction to the reporting application
  • Creating list reports
  • Using filters
  • Create crosstab reports
  • Graphical data
  • Using prompts
  • Using calculations
  • Conditional formatting
  • Drill-Throughs
  • Using relational data
  • Administration
  • Architecture
  • Secure the environment
  • Managing run activities
  • Managing content in administration

Audience:

This advanced course is for:

  • Project Managers
  • Technical Analysts
  • Developers

Overview of IBM Cognos BI

  • Describe IBM Cognos Business Intelligence (BI) and its position within the IBM Smarter Analytics approach and offerings
  • Describe the IBM Cognos 10 Family of offerings
  • Describe IBM Cognos BI enterprise components
  • Describe IBM Cognos architecture at a high level
  • Describe IBM Cognos BI security at a high level
  • Explain how to extend IBM Cognos BI

Identify Common Data Structures

  • Define the role of a metadata model in Cognos BI
  • 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

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

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

Preparing Reusable Metadata

  • Verify relationships and query item properties
  • Create 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 uses cardinality
  • Identify reporting traps
  • Use tools to analyze the model

Model 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

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

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

Specifying Determinants

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

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
  • Rapidly create a model using the Model Design Accelerator

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

Introduction to the Reporting Application

  • Examine Report Studio and its interface
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