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This course 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 in Cognos Analytics 11. 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.



Highlights:
  • Overview of IBM Cognos Analytics
  • Common data structures
  • Requirements and projects
  • Reusable metadata
  • Establishing predictable results
  • Using calculations and filters
  • Time dimension
  • Specifying determinants
  • Establishing the presentation view
  • Query subject types
  • Security
  • Creating objects
  • Managing OLAP data sources
  • SQL concepts and queries
  • Using advanced parameterization
  • Maintenance
  • Optimizing and tuning models
  • Multi-Modeler environment
  • Managing packages�

While class exercises are performed within a Cognos Analytics v11 environment, our expert instructors can provide guidance on all versions and their differences.


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


Audience:

Developers who design metadata models for use in IBM Cognos Analytics


1. Introduction to IBM Cognos Analytics

  • Describe IBM Cognos Analytics and its position within an analytics solution
  • Describe IBM Cognos Analytics components
  • Describe IBM Cognos Analytics at a high level
  • Explain how to extend IBM Cognos

2. Identifying Common Data Structures

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

3. 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

4. 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

5. Preparing Reusable Metadata

  • Verify relationships and query item properties
  • Create efficient filters by configuring prompt properties

6. Modeling for Predictable Results: Identifying 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

7. Modeling 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

8. Modeling for Predictable Results: Consolidate Metadata

  • 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. Creating 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. 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

11. Specifying Determinants

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

12. 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
  • Rapidly create a model using the Model Design Accelerator

13. Working with Different Query Subject Types

  • Identify the effects of modifying query subjects on generated SQL
  • Specify two types of stored procedure query subjects
  • Use prompt values to accept user input

14. Setting Security in Framework Manager

  • Examine the IBM Cognos security environment
  • Restrict access to packages
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Virtual Live3/12/2018 8:30:00 AM<span class="course-type type-v" style="cursor:default;word-wrap:normal;display:inline-block;" onmouseover="showHoverInfo(this, 'ProductTypeDescription' ,'VILT')" onmouseout="clearHoverInfo()">V</span>5 days3795.002458635
Virtual Live4/30/2018 8:30:00 AM<span class="course-type type-v" style="cursor:default;word-wrap:normal;display:inline-block;" onmouseover="showHoverInfo(this, 'ProductTypeDescription' ,'VILT')" onmouseout="clearHoverInfo()">V</span>5 days3795.002458632
Virtual Live6/4/2018 11:30:00 AM<span class="course-type type-v" style="cursor:default;word-wrap:normal;display:inline-block;" onmouseover="showHoverInfo(this, 'ProductTypeDescription' ,'VILT')" onmouseout="clearHoverInfo()">V</span>5 days3795.002458637
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