IBM Cognos Dynamic Cubes

IBM Cognos Dynamic Cubes

by Dmitriy Beryoza, Shilpa Bhimavarapu, Alan Blake, David Cushing, Vlaunir Da Silva, Mario Daigle, Avery Hagleitner, Ian Henderson, Beth Jubera, Skyla Loomis, Chris McPherson, Steven Rogers, Carlos Ruiz, Christopher Yao
Released October 2012
Publisher(s): IBM Redbooks
ISBN: None

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Book description

IBM® Cognos® Business Intelligence (BI) provides a proven enterprise BI platform with an open data strategy, providing customers with the ability to leverage data from any source, package it into a business model, and make it available to consumers in various interfaces that are tailored to the task.

IBM Cognos Dynamic Cubes complements the existing Cognos BI capabilities and continues the tradition of an open data model. It focuses on extending the scalability of the IBM Cognos platform to enable speed-of-thought analytics over terabytes of enterprise data, without having to invest in a new data warehouse appliance. This capability adds a new level of query intelligence so you can unleash the power of your enterprise data warehouse.

This IBM Redbooks® publication addresses IBM Cognos Business Intelligence V10.2 and specifically, the IBM Cognos Dynamic Cubes capabilities. This book can help you in the following ways:

  • Understand core features of the Dynamic Cubes capabilities of IBM Cognos BI V10.2

  • Learn by example with practical scenarios using the IBM Cognos samples


This book uses fictional business scenarios to demonstrate the power and capabilities of IBM Cognos Dynamic Cubes. It primarily focuses on the roles of modeler, administrator, and IT architect.

Table of contents

  1. Notices
    1. Trademarks
  2. Preface
    1. The team who wrote this book
    2. Now you can become a published author, too
    3. Comments welcome
    4. Stay connected to IBM Redbooks
  3. Chapter 1: Overview of Cognos Dynamic Cubes
    1. Introduction to IBM Cognos Dynamic Cubes
      1. High performance interactive analysis
      2. Enterprise data warehouses for analytics
      3. Data volumes and context in the Enterprise Data Warehouse
      4. Architecture summary
    2. Skillset requirements for IBM Cognos Dynamic Cubes
      1. Modeling
      2. Cognos administration
      3. Infrastructure design
    3. When to use Cognos Dynamic Cubes
    4. System requirements
    5. Comparison to other IBM cube technologies
  4. Chapter 2: IBM Cognos Dynamic Cubes architecture
    1. Dynamic cubes in the IBM Cognos environment
      1. Dynamic cubes and the data warehouse
      2. Modeling dynamic cubes
      3. Dynamic cubes as data sources
      4. Configuring dynamic cubes
      5. Dynamic cube management
      6. Virtual cubes
      7. Aggregate Advisor
    2. Dynamic cubes and the Dynamic Query Mode server
      1. Dynamic cubes and report server
      2. Dynamic cubes within the Dynamic Query Mode server
    3. Cognos Dynamic Cubes caching
      1. Result set cache
      2. Expression cache
      3. Member cache
      4. Aggregate cache
      5. Data cache
    4. Dynamic cubes query processing
      1. Metadata query processing in the Dynamic Query Mode server
      2. OLAP query processing in the Dynamic Query Mode server
    5. Using the database to evaluate set expressions
    6. Management of Cognos Dynamic Cubes
  5. Chapter 3: Installation and configuration of Cognos Cube Designer and Dynamic Query Analyzer
    1. Introduction
    2. Cognos Cube Designer operating requirements
      1. IBM Cognos 10.2 Business Intelligence Server
      2. IBM Cognos 10.2 Report Server
      3. IBM Cognos 10.2 Framework Manager
      4. Java Runtime Environment Libraries
      5. Supported relational databases
      6. Cognos Cube Designer supported operating systems
    3. Cognos Dynamic Cubes hardware requirements for the BI Server
    4. Installing IBM Cognos Cube Designer
    5. Installing Dynamic Query Analyzer
      1. Dynamic Query Analyzer installation requirements
      2. Installation procedure (1/2)
      3. Installation procedure (2/2)
      4. Configuring Dynamic Query Analyzer
  6. Chapter 4: Modeling dynamic cubes
    1. Introduction to IBM Cognos Cube Designer
    2. Working with Cognos Cube Designer
      1. Launching Cognos Cube Designer
      2. Creating a new project
      3. The Cognos Cube Designer workspace
      4. Creating calculated measures
      5. Importing metadata
      6. Exploring data using the Relational Explorer Diagram
      7. Exploring data using the tabular data view
      8. Creating a dynamic cube
    3. Modeling dimensions
      1. Relationships
      2. Modeling levels
      3. Member tree organization options
      4. Modeling level keys
      5. Parent-child dimensions
    4. Calculated members
    5. Modeling time dimensions for relative time
      1. Using relative time
    6. Slowly changing dimensions
      1. Modeling slowly changing dimensions
      2. Metadata discovery
      3. Slowly changing dimension as a parent-child dimension
      4. Modeling a slowly changing dimension in a regular dimension
    7. Role-playing dimensions
    8. Multi-grain fact scenarios
    9. Aggregate cubes
      1. Modeling aggregate cubes
      2. Degenerate dimensions with matching level keys
      3. Degenerate dimensions with matching join keys
      4. Rolled-up dimensions
      5. Parent-child dimensions
      6. Custom aggregation
      7. Slicers
      8. Other modeling considerations
      9. Automatic aggregate cube creation
    10. Validation
    11. Deploying dynamic cubes for reporting and analysis
      1. Quick-deploy options in Cognos Cube Designer
      2. Manually deploying a dynamic cube
    12. Troubleshooting
      1. Importing metadata
      2. Publishing errors
      3. Missing metadata
      4. Refreshing metadata that changed in the database
      5. Members
      6. Missing members
      7. Ellipses in the project viewer tree
      8. The No Protocol message while running Cognos Cube Designer
    13. Creating a sample cube model by using GOSLDW
      1. Measures of gosldw_sales
      2. Dimensions in the gosldw_sales cube
      3. Time
      4. Employee by region
      5. Promotions
      6. Order method
      7. Retailers
      8. Time (close date)
      9. Time (ship date)
      10. Branch
      11. Product brand
      12. Product name
      13. Products
    14. Creating a time dimension
    15. Modeling for multi-grain scenarios
  7. Chapter 5: Administering dynamic cubes
    1. Adding and removing cubes from the QueryService
      1. Adding a cube to the QueryService
      2. Removing a cube from the QueryService
    2. Starting, stopping, and monitoring cubes
      1. Starting a cube
      2. Stopping a cube
      3. Monitoring cube state through metrics
    3. Managing the cache
    4. Setting up routing rules
    5. Setting up redundant cube instances
    6. Scheduling a refresh of the cache (1/2)
    7. Scheduling a refresh of the cache (2/2)
  8. Chapter 6: Virtual cubes
    1. Overview of virtual cubes
    2. Creating virtual cubes
      1. Deploying virtual cubes
      2. Manually merging source cube objects
    3. Common use cases for virtual cubes
      1. Time partitioning
      2. Currency conversion
      3. Multiple fact tables
    4. Managing virtual cubes
      1. Verifying virtual cube dependency
      2. Starting the virtual cube
      3. Stopping the virtual cube
      4. Stopping the source cubes
    5. Virtual cube considerations
      1. Modeling considerations for virtual cubes
      2. Caching and performance considerations
  9. Chapter 7: Dimensional security
    1. Overview of dimensional security
    2. Security model
      1. Security filters
      2. Security views
    3. Grant versus deny approaches to security
    4. Visible ancestors
      1. Example: Visible ancestors unnecessary
      2. Example: Basic visible ancestor
      3. Example: Combination of visible and granted ancestors
      4. Examples: View merge impact on visible ancestors (1/2)
      5. Examples: View merge impact on visible ancestors (2/2)
    5. Secured padding members
      1. Example: Secured padding member unnecessary
      2. Example: Secured padding member needed at leaf level
      3. Example: Secured padding members needed on multiple levels
    6. Default members
      1. Default member examples
      2. Data caching
    7. Calculated members
    8. Merging of security views or security filters
      1. Secured tuples
      2. Example 1
      3. Example 2
      4. Example 3
      5. Example 4
      6. Example 5
      7. Example 6
      8. Example 7
    9. Defining security in Cognos Cube Designer
      1. Selecting the hierarchy on which to define the security filter
      2. Creating security filters
      3. Creating security views
      4. Securing measures
    10. Publish and start the cube
    11. Applying security views
    12. Verifying the security model
  10. Chapter 8: Optimization and performance tuning
    1. Performance implications of OLAP-style reports
    2. Aggregate awareness in Cognos Dynamic Cubes
    3. Overview of the Aggregate Advisor
      1. Model-based analysis
      2. Workload-based analysis
      3. Running the Aggregate Advisor without considering workload information (1/2)
      4. Running the Aggregate Advisor without considering workload information (2/2)
      5. Running the Aggregate Advisor with considering workload information
      6. Opening Aggregate Advisor results and viewing details (1/2)
      7. Opening Aggregate Advisor results and viewing details (2/2)
      8. Rerunning the Aggregate Advisor
    4. In-memory aggregates
      1. Applying in-memory aggregates
      2. Loading in-memory aggregates into the aggregate cache
      3. Monitoring aggregate cache hits
      4. In-memory aggregate tips and troubleshooting
    5. Database aggregates
      1. In-database aggregate recommendations
      2. Creating recommended database aggregates
      3. Maintaining database aggregates
      4. Monitoring database aggregate table hits
      5. Database aggregates tips and troubleshooting
    6. Cache Priming Techniques
      1. Preloading the caches
      2. Priming the caches
    7. Cache size best practices
    8. Scenarios for performance tuning
      1. Cases for adjusting cache sizes
      2. Cases for aggregates
  11. Chapter 9: Dynamic cube lifecycle
    1. Overview of the dynamic cube lifecycle
      1. Analyze
      2. Model
      3. Deploy
      4. Run
      5. Optimize
    2. Lifecycle across different environments
      1. Mechanisms for moving dynamic cubes
      2. Development
      3. Test
      4. Production
    3. Best practices for deploying between environments
      1. Keep a copy of the dynamic cube project file under source control
      2. Use consistent data source, schema, and table names in all environments
      3. Skip the optimize step in the development environment
      4. Use a separate database for each environment
      5. Include complete dimensional data in development environment
      6. Make the test system similar to the production system
  12. Chapter 10: Troubleshooting
    1. Dynamic Query Analyzer
      1. New Features
      2. Configuring Dynamic Query Analyzer
      3. Query execution tracing
    2. Visualizing dynamic cube startup
    3. Reviewing Cognos reports with Dynamic Query Analyzer
      1. Reviewing the query execution trace
      2. Subsequent run requests: Taking advantage of the result set cache
      3. Confirming the role of caching
      4. Reviewing Report SQL
      5. Verifying changes to the BranchProfitByYear Report
    4. Virtual cube query execution tracing
    5. Dynamic cube QueryService logging
    6. Dynamic cube query plan tracing
    7. Aggregate matching
    8. Common problems
      1. Configuring Cognos Dynamic Cubes logging
      2. Cube does not start
      3. Unexpected data values returned
      4. Cube loaded but relative time members are missing
  13. Related publications
    1. IBM Redbooks
    2. Online resources
    3. Help from IBM
  14. Back cover

Product information

  • Title: IBM Cognos Dynamic Cubes
  • Author(s): Dmitriy Beryoza, Shilpa Bhimavarapu, Alan Blake, David Cushing, Vlaunir Da Silva, Mario Daigle, Avery Hagleitner, Ian Henderson, Beth Jubera, Skyla Loomis, Chris McPherson, Steven Rogers, Carlos Ruiz, Christopher Yao
  • Release date: October 2012
  • Publisher(s): IBM Redbooks
  • ISBN: None