IBM COGNOS FRAMEWORK MANAGER Training

 >>  IBM COGNOS FRAMEWORK MANAGER Training

IBM COGNOS FRAMEWORK MANAGER Training


 (5) | 750 Ratings


Introduction


IBM COGNOS FRAMEWORK MANAGER Training Details
Track Regular Track Weekend Track Fast Track
Course Duration 30 Hrs 8 Weekends 5 Days
Hours 1hr/day 2 Hours a day 6 Hours a day
Training Mode Online Classroom Online Classroom Online Classroom
Delivery Instructor Led-Live Instructor Led-Live Instructor Led-Live


Course Curriculum

IBM Cognos Framework Manager Online Training

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

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

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

 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

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

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

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

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
  • Rapidly create a model using the Model Design Accelerator

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

Setting Security in Framework Manager

  • Examine the IBM Cognos security environment
  • Restrict access to packages
  • Create and apply security filters
  • Restrict access to objects in the model

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

Managing 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

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 IBM Cognos Analytics - Reporting generated SQL
  • Dimensionally modeled relational SQL generation
  • Cross join SQL
  • Various results sets for multi-fact queries

Using advanced parameterization techniques in Framework Manager

  • Identify environment and model session 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
  • Create a model report

Optimizing and tuning Framework Manager models

  • Identify how minimized SQL affects model performance
  • Use governors to set limits on query execution
  • Identify the impact of rollup processing on aggregation
  • Apply design mode filters
  • Limit the number of data source connections
  • Use the quality of service indicator

Working in a Multi-Modeler Environment

  • Segment and link a project
  • Branch a project and merge results

Managing packages in Framework Manager

  • Specify package languages and function sets
  • Control model versioning
  • Nest packages
  • Appendix A. Additional modeling techniques
  • Leverage a user defined function
  • Identify the purpose of query sets
  • Use source control to manage Framework Manager files
  • Appendix B. Modeling multilingual metadata
  • Customize metadata for a multilingual audience

Exam & Certification

0

Course Review

(5)
5 stars
4 stars
3 stars
2 stars
1 stars

Course Curriculum

IBM Cognos Framework Manager Online Training

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

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

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

 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

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

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

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

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
  • Rapidly create a model using the Model Design Accelerator

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

Setting Security in Framework Manager

  • Examine the IBM Cognos security environment
  • Restrict access to packages
  • Create and apply security filters
  • Restrict access to objects in the model

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

Managing 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

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 IBM Cognos Analytics - Reporting generated SQL
  • Dimensionally modeled relational SQL generation
  • Cross join SQL
  • Various results sets for multi-fact queries

Using advanced parameterization techniques in Framework Manager

  • Identify environment and model session 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
  • Create a model report

Optimizing and tuning Framework Manager models

  • Identify how minimized SQL affects model performance
  • Use governors to set limits on query execution
  • Identify the impact of rollup processing on aggregation
  • Apply design mode filters
  • Limit the number of data source connections
  • Use the quality of service indicator

Working in a Multi-Modeler Environment

  • Segment and link a project
  • Branch a project and merge results

Managing packages in Framework Manager

  • Specify package languages and function sets
  • Control model versioning
  • Nest packages
  • Appendix A. Additional modeling techniques
  • Leverage a user defined function
  • Identify the purpose of query sets
  • Use source control to manage Framework Manager files
  • Appendix B. Modeling multilingual metadata
  • Customize metadata for a multilingual audience

    Click here for Help and Support: info@sacrostectservices.com     For Inquiry Call Us:   +91 996-629-7972(IND)

  +91 996-629-7972(IND)
X

Quick Enquiry

X

Business Enquiry