Contains: PDF course guide, as well as a lab environment where students can work through demonstrations and exercises at their own pace. This course provides participants with introductory to advanced knowledge of how to model metadata for predictable reporting and analysis results using IBM Cognos Cube Designer. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing a dynamic cube, and enabling end users to easily author reports and analyze data. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course. Terms and Conditions: Ingram Micro – https://www.ingrammicrotraining.com/Terms-of-use.aspx; IBM – http://www.ibm.com/training/terms

Version:

v11.0

Audience:

Data Modelers

Objectives:

Detail:

lly
? Aggregate Advisor recommendations
? Monitor Dynamic Cube performance
? Model aggregates (automatically vs manually)
? Use Slicers to define aggregation partitions

7: Define Security
? Overview of Dynamic Cube security
? Identify security filters
? The Security process – Three steps
? Examine security scope
? Identify scope rules
? Identify roles
? Capabilities and access permissions
? Cube security deep dive

8: Model a virtual cube
? Explore virtual cubes
? Create the virtual cube
? Explore virtual cube objects
? Examine virtual measures and calculated members
? Currency conversion using virtual cubes
? Security on virtual cubes

A: Introduction to IBM Cognos Analytics (Optional)
? Define IBM Cognos Analytics
? Redefined Business Intelligence
? Self-service
? Navigate to content in IBM Cognos Analytics
? Interact with the user interface
? Model data with IBM Cognos Analytics
? IBM Cognos Analytics components
? Create reports
? Perform self-service with analysis and Dashboards
? IBM Cognos Analytics architecture (high level)
? IBM Cognos Analytics security
? Package / data source relationship
? Create Data modules
? Upload files

Pre-Requisites:

? Knowledge of dimensional modeling and design. Experience using the IBM Cognos Analytics portal and Administration.