Profit and Loss Measure Dimension

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The measures in the Profit and Loss Measure Dimension contains all the information on Calculations and Data Validation of the Profit and Loss Cube.

The base elements and their direct parents in the Data Validations, Data Validation Errors, and Data Validation Warnings hierarchies are configurable. Each data validation is represented by a base element with a name DVnnn under Data Validations where nnn is a three-digit number. For these elements, the Calculation, CalculationDependencies, and TargetRestriction attribute values define the data validation by returning a non-zero value for any failed validation (see CF Account Dimension ). Passed data validation should return preferably NULL or 0.

For each data validation there must be one base element with a name DVnnn_E under Data Validations Errors and another base element with a name DVnnn_W under Data Validations Warnings. These should not have any attribute values.

- Data validations and their corresponding elements in the Data Validation Errors and Data Validation Warnings hierarchies should be grouped by consolidated elements with names DVnxx" "DVxnnx" to address groups of data validations in reports and the workflow.

The Profit and Loss Measure Dimension can be configured through their attributes:

Attribute Description
Name

Readable name of the account. Localized translations can be provided. This attribute is visible in the report. There is no hard-coded behavior implemented in this attribute (string).
Description

Long text description of the account. This attribute can contain a definition of the amounts booked to the account or instructions for the planners. Localized translations can be provided (string).
Calculation Defines the calculation for the element.

CalculationDependencies

 Indicates which cube is the source of transferred data.
TargetRestriction Slice within one or more of the business dimensions receiving transferred data.
Data Validation Threshold An optional positive numeric value to suppress any failed Data Validation below the threshold value.
Data Validation Severity Must be either Error or Warning. Errors will stop the workflow whilst Warnings will be shown but would not block the workflow.
:nodetype

Make sure you do not delete the following elements:

  • Value

  • Comment

  • Data Validations

  • Data Validation Errors

  • Data Validation Warnings

Updated September 25, 2024