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IBM Cognos Cube Designer - Design Dynamic Cubes (v11.0)
This course provides participants with introductory to advanced knowledge of how to model metadata for predictable reporting and analysis results using IBM Cognos Cube Designer. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing a dynamic cube, and enabling end users to easily author reports and analyze data.
Please refer to course overview
• Knowledge of dimensional modeling and design. Experience using the IBM Cognos Analytics portal and Administration.
1: Introduction to IBM Cognos Dynamic Cubes
• Define and differentiate Dynamic Cubes
• Dynamic Cubes characteristics
• Examine Dynamic Cube requirements
• Examine Dynamic Cube components
• Examine high level architecture
• IBM Cognos Dynamic Query
• Review Dimensional Data Structures
• Dynamic Cubes caching
2: Create and design a Dynamic Cube
• Explore the IBM Cognos Cube Designer
• Review the cube development process
• Examine the Automatic Cube Generation
• Manual development overview
• Create dimensions
• Model the cube
• Best practice for effective modeling
3: Deploy and configure a Dynamic Cube
• Deploy a cube
• Explore the Estimate Hardware Requirements
• Identify cube management tasks
• Examine Query Service administration
• Explore Dynamic Cube properties
• Schedule cube actions
• Use the DCAdmin comment line tool
4: Advanced Dynamic Cube modeling
• Examine advanced modeling concepts
• Explore modeling caveats
• Calculated measures and members
• Model Relative Time
• Explore the Current Period property
• Define period aggregation rules for measures
5:Advanced features of Cube Designer
• Examine multilingual support
• Examine ragged hierarchies and padding members
• Define Parent-Child Dimensions
• Refresh Metadata
• Import Framework Manager packages
• Filter measures and dimensions
6: Optimize performance with aggregates
• Identify aggregates and aggregate tables
• In-memory aggregates
• Use Aggregate Advisor to identify aggregates
• User defined in-memory aggregates
• Optimize In-Memory Aggregates automatically
• Aggregate Advisor recommendations
• Monitor Dynamic Cube performance
• Model aggregates (automatically vs manually)
• Use Slicers to define aggregation partitions
7: Define Security
• Overview of Dynamic Cube security
• Identify security filters
• The Security process - Three steps
• Examine security scope
• Identify scope rules
• Identify roles
• Capabilities and access permissions
• Cube security deep dive
8: Model a virtual cube
• Explore virtual cubes
• Create the virtual cube
• Explore virtual cube objects
• Examine virtual measures and calculated members
• Currency conversion using virtual cubes
• Security on virtual cubes
A: Introduction to IBM Cognos Analytics (Optional)
• Define IBM Cognos Analytics
• Redefined Business Intelligence
• Navigate to content in IBM Cognos Analytics
• Interact with the user interface
• Model data with IBM Cognos Analytics
• IBM Cognos Analytics components
• Create reports
• Perform self-service with analysis and Dashboards
• IBM Cognos Analytics architecture (high level)
• IBM Cognos Analytics security
• Package / data source relationship
• Create Data modules
• Upload files
When you complete the Instructor-Led version of this course, you will be eligible to earn an IBM Training Badge that can be displayed on your website, business cards, and social media channels to demonstrate your mastery of the skills you learned here.Learn more about our IBM Cognos Badge Program →
Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
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Self-Paced Training Terms & Conditions
THIS IS A SELF-PACED VIRTUAL CLASS. AFTER YOU REGISTER, YOU HAVE 30 DAYS TO COMPLETE THE COURSE.
This is a Self-Paced virtual class; it is intended for students who do not need the support of a classroom instructor. If you feel you would better benefit from having access to a Subject Matter Expert, please enroll in the Instructor-Led version instead. Minimal technical support is provided to address issues with accessing the platform or problems within the lab environment.
Before you enroll, review the system requirements to ensure that your system meets the minimum requirements for this course. AFTER YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT. You are billed for the course when you submit the enrollment form. Self-Paced Virtual Classes are non-refundable. Once you purchase a Self-Paced Virtual Class, you will be charged the full price.
After you receive confirmation that you are enrolled, you will be sent further instructions to access your course material and remote labs. A confirmation email will contain your online link, your ID and password, and additional instructions for starting the course.
You can start the course at any time within 12 months of enrolling for the course. After you register/start the course, you have 30 days to complete your course. Within this 30 days, the self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day.
If the course requires a remote lab system, the lab system access is allocated on a first-come, first-served basis. When you are not using the elab system, ensure that you suspend your elab to maximize your hours available to use the elab system.
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