When does class start/end?
Classes begin promptly at 9:00 am, and typically end at 5:00 pm.
This IBM Self-Paced Virtual Class (SPVC) includes: - PDF course guide available to attendee during and after course - Lab environment where students can work through demonstrations and exercises at...Read More
This IBM Self-Paced Virtual Class (SPVC) includes:
- PDF course guide available to attendee during and after course
- Lab environment where students can work through demonstrations and exercises at their own pace
Contains: PDF course guide, as well as a lab environment where students can work through demonstrations and exercises at their own pace.
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.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course. /terms
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 caching2: 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 modeling3: 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 tool4: 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 measures5: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 partitions7: 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 dive8: 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 cubesA: Introduction to IBM Cognos Analytics (Optional)- Define IBM Cognos Analytics- Redefined Business Intelligence- Self-service- 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
Save up to $250-$2500 Use Promo Code: SurfBoard
View Details Register by September 6, 2019