Model in Planning Analytics Workspace
IBM® Planning Analytics Workspace includes a modeling environment that you can use to model user data with cubes, dimensions, hierarchies, attributes, and security for IBM Planning Analytics with Watson™.
OLAP modeling and modeling concepts can be confusing. This video will help you to understand some of the basic concepts of what they are and why we model data for analyzes:
You can use the Planning Analytics Workspace modeling tools to convert business requirements into precise cubes, dimensions, hierarchies, and calculations so that planning and analytics outcomes make sense to business users.
- Build and maintain the structure of a financial model independently, without coding.
- Transform and load data easily into a financial model, which increases transparency and confidence in results.
- Build a step-by-step financial process for multiple users based on roles and security permissions, without coding.
- Modelers can define business logic by using an integrated development environment.
To use Planning Analytics Workspace modeling, you must log in with a user name that has the Modeler role.
Planning Analytics Workspace modeling supports the following tasks:
- Creating cubes
- Using rules
- Editing dimensions
- Managing hierarchies
- Creating attributes
- Managing security
To understand why you should use the Planning Analytics Workspace tools to model your data, consider the following benefits.
You can create more manageable dimensions by creating more than one hierarchy in a dimension.
For example, you can create a single time dimension. A year dimension must be the same for every year to compare data between two years. This approach gives you the ability to create a new year easily, and query performance is faster because you have only one dimension in the cube.
You can create a time dimension with multiple hierarchies that represent years and months to do yearly comparisons per month.
If you create two dimensions, one for year and one for months, you gain the ability to split the years and months across two axes and you can compare data between years.
Using hierarchies to add versions creates flexibility. For example, you might need to change your organizational hierarchy for planned changes. One dimension might be the organization and you can use hierarchies in the dimension to represent the organization in the future year. This hierarchy might represent the data differently from the previous year's hierarchy. With multiple hierarchies that represent the organization, you can roll up the data in multiple ways.
Hierarchies are named and contain members. You can reuse the same consolidated members in multiple hierarchies. You can use hierarchies to group these members without the need for specific consolidated names.
Hierarchies conform to OLAP Industry standards. Planning Analytics Workspace modeling uses MDX and TM1 REST APIs to access TM1 data. The TM1 REST APIs support the hierarchy model and follow the ODATA standard.