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IBM Cognos Framework Manager Basic

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Duration: 3 Days

Method: Delivery Method: Instructor led, Hands-on workshops

Price: $1800.00

Course Code: CG1008



Audience

This metadata modeling course is best fitted for the following audiences: New to both metadata modeling and data warehousing, Upgrading from previous versions, Knowledge refresher

Description

Millions of dollars are wasted every year on Business Intelligence implementations that fail to provide a clear strategic architecture to presenting corporate information for end user consumption. If the data is organized in a concise, consistent manner, and performs well, the project will be well received and accepted around the organization. In order to achieve this, a solid understanding of the IBM Cognos Framework Manager tool is necessary.

Based on a proven training curriculum, we will provide instructor-led classes that highlight the important steps to be considered during the design and implementation process of a Framework model.

During the session, students will be introduced to the entire Framework Manager lifecycle, beginning with the planning phase, all the way through to publishing the model for user consumption. Each topic will be highlighted with in-depth workshops, Q&A sessions and tips and techniques drawn from over 15 plus years of cross industry experience.

The curriculum is based on the most recent version of IBM Cognos Framework Manager, and uses the sample data sources included in the IBM Cognos BI Samples package. All our instructors are IBM Cognos certified relational data modelers. They also provide the benefit of having up to 15 years of real-world experience.

Prerequisites

A good comprehension of Microsoft Windows is mandatory in order to navigate. An understanding of the standard IBM Cognos BI portal (Cognos Connection) is a benefit.

Topics

  1. Framework Manager Overview
  2. Access your Data
  3. Framework Manager Objects and Terminology
  4. Create Packages
  5. Organize your Projects
  6. Generating and Creating Relationships
  7. Filters
  8. Calculations
  9. Work with Dimensionally Modeled Data
  10. Durable Models
  11. Model Design Accelerator
  12. Extra Features