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IBM Cognos Framework Manager

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IBM Cognos Framework Manager  Training in Bangalore- Live Online & Classroom

 

myTectra offers IBM Cognos Framework Manager Training in Bangalore,Chennai, Pune using Class Room.myTectra offers Live Online IBM Cognos Framework Manager Training Globally

 

IBM Cognos Framework Manager Training will train you and provide you with the Cognos Architecture with
the information and logic required to access many data sources. Based on an authenticated training curriculum,
our trainers will highlight the essential steps to be examined during the design and implementation of
Framework model. This course offers the participants with advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using Framework Manager. Participantswill be able to learn the full scope of the metadata modeling process enabling end users to analyze data and author reports.myTectra offers Live Online IBM Cognos Framework Manager Training Globally

 

Course Content

 

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

 

 

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myTectra flexible batch schedules enables you to start your class at your convenient date and time.


1. All the enrolled candidates must start the class by any date within 30 days from the date of enrollment.
2. Maximum of 3 Days will be taken by myTectra to schedule the batches from the date of schedule request from the candidate.
3. Individual Focus - Maximum 5 candidates allowed per batches
4. The candidate can request any one of the batch time slot from the below list
Batch Type Time Slab Hours/Day Time Zone Days
Regular Morning 6.30 AM - 9.30 AM Anytime Maximum 2 Hrs IST Monday-to-Friday
Regular Evening 6.30 PM - 9.30 PM Anytime Maximum 2 Hrs IST Monday-to-Friday
Week End 6.30 AM - 9.30 PM Anytime Maximum 3 Hrs IST Saturday,Sunday
Fast Track-Morning 6.30 AM - 9.30 AM Anytime Maximum 2 Hrs IST Monday-to-Saturday
Fast Track-Evening 6.30 PM - 9.30 PM Anytime Maximum 2 Hrs IST Monday-to-Saturday
Customized Batch Customized Timing Customized Hrs IST Customized Days

Note : We can schedule your batch anytime on Saturday and Sunday between 6.30 AM 9.30 PM at your convenient time


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