This accelerated offering is intended for core project team members wanting to acquire a broad understanding of IBM Cognos Analytic platform implementation. During the ILT segments, participants will perform hands-on demonstrations and exercises that cover three essential topic areas: modeling, report authoring, and administration of IBM Cognos Analytics. During the WBT portion of the course, students will be required to complete 16.5 hours of eLearning (6 WBTs and 1 recording).

eLearning:

• B5130G - IBM Cognos for Microsoft Office: Integrate with Microsoft Office (v10.1/10.2)
• B5231G - IBM Cognos BI Event Studio: Create and Manage Agents (v8.4/10.1)
• B5169G - IBM Cognos Transformer: Create PowerCubes (v10.1)
• B6088G - IBM Cognos Analytics for Consumers (v11.0)
• B6089G - IBM Cognos Analytics: Create Dashboards (v11.0)
• B6090G - IBM Cognos Analytics: Create Data Modules (v11.0)
• B6091G - IBM Cognos Analytics: Departmental Administration (v11.0)

Please refer to course overview.

Core Project Team members
• Project Managers
• Technical Analysts
• Developers

• Knowledge of common industry-standard data structures and design.
• Experience with SQL
• Experience gathering requirements and analyzing data.
• Knowledge of Web application server architectures
• Security systems administration
• Knowledge of your business requirements
• Experience using the Windows operating system
• Experience using a web browser

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 Analytics
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
13: 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
14: Introduction to IBM Cognos Analytics - Reporting
• Examine IBM Cognos Analytics - Reporting and its interface
• Explore different report types
• Create reports in preview or design mode
• Create a simple, sorted, and formatted report
• Examine dimensionally modelled and dimensional data sources
• Explore how data items are added queries
• Examine personal data sources and data modules
15: Creating list reports
• Group, format, and sort list reports
• Describe options for aggregating data
• Create a multi-fact query
• Create a report with repeated data
16: Focusing reports using filters
• Create filters to narrow the focus of reports
• Examine detail filters and summary filters
• Determine when to apply filters on aggregate data
17: Creating crosstab reports
• Format and sort crosstab reports
• Create complex crosstabs using drag and drop functionality
• Create crosstabs using unrelated data items
18: Present data graphically
• Create charts containing peer and nested columns
• Present data using different chart type options
• Add context to charts
• Create and reuse custom chart palettes
• Introduce visualization
• Present key data in a single dashboard report
19: Focusing Reports Using Prompts
• Identify various prompt types
• Use parameters and prompts to focus data
• Search for prompt types
• Navigate between pages
20: Extend reports using calculations
• Create calculations based on data in the data source
• Add run-time information to the reports
• Create expressions using functions
21: Customizing reports with conditional formatting
• Create multi-lingual reports
• Highlight exceptional data
• Show and hide data
• Conditionally render objects in reports
• Conditionally format one crosstab measure based on another
22 Drill-through definitions
• Discuss parameter-driven drill through
• Discuss dynamic drill through
• Set up package-based drill-through definitions
• Set scope
• Use the Drill Through Assistant
23 Introduction to IBM Cognos BI Administration
• IBM Cognos Analytics enterprise components
• Role of the Administrator in relation to the IBM Cognos Analytics administration workflow process
• Role of IBM Cognos Administration and IBM Cognos Configuration
24 Identifying IBM Cognos architecture
• The features of the IBM Cognos Analytics architecture
• The three architectural tiers
• IBM Cognos Analytics servlets and services
• The default servlet container and alternatives to its use
• An example of IBM Cognos Analytics request processing
• Installation options
• Load balancing mechanisms
• Configuration options
• The IBM Cognos Application Firewall
25: Securing the IBM Cognos Analytics environment
• Identify the IBM Cognos Analytics security model
• Define authentication in IBM Cognos Analytics
• Define authorization in IBM Cognos Analytics
• Identify security policies
• Secure the IBM Cognos Analytics environment
26: Managing run activities
• Manage current, upcoming and past activities
• Manage schedules
• Enable and disable schedules
• Set queue priority for schedules
• Suspend a schedule until a later time
27: Managing content in IBM Cognos Administration
• Add a data source
• Distribute data and create a distribution list
• Add visualizations to the Library
• Plan and perform a deployment
• Identify how to maintain the IBM Cognos Analytics content store
• Configure saving content outside of the content store
• Customize the appearance of IBM Cognos Analytics using styles
• Use portlets to display custom Web content