Create Attribute Dimensions and Members
Attributes describe characteristics of Essbase data, such as the size and color of products. You can use attributes to group and analyze members of dimensions based on their characteristics.
For example, you can analyze product profitability based on size or packaging, and you can make more effective conclusions by incorporating market attributes, such as the population size of each market region, into your analysis.
Workflow for manually building attribute dimensions:
When manually working with attributes in the Redwood Interface, use the outline editor and the Add Member(s) dialog box in the outline editor.
- Create dimensions with the dimension type of attribute. While
in the Add Members dialog box,
- Set the attribute dimension type (text, numeric, Boolean, or date).
- Associate a standard dimension with an attribute dimension, thereby defining the base dimension of the attribute dimension.
- Add members to the attribute dimensions.
When manually working with attributes in the Classic Web Interface, use the outline editor and the Attributes tab in the outline inspector.
- Create attribute dimensions.
- Tag the dimensions as attribute dimensions and set the attribute dimension
type (text, numeric, Boolean, or date).
Use the outline inspector, general tab to set the dimension as an attribute dimension, and to set the attribute dimension type.
- Add members to attribute dimensions.
- Associate a standard dimension with an attribute dimension, thereby defining the base dimension of the attribute dimension. Use the Attributes tab in the outline inspector to associate an attribute dimension to a base dimension.
When creating an attribute dimension, by default, a base dimension is associated with the newly created attribute dimension. The associated base dimension is either a newly created last sparse dimension or the last existing sparse dimension.
For example, if you create two sparse dimensions, dim1 and dim2, and then create an attribute dimension attr1, attr1 is associated with dim2 (the last sparse dimension that was created). If no sparse dimension was created recently, attr1 is associated with the last sparse dimension.