All measures that record a static level (inventory levels, financial account balances, and measures of intensity such as room temperatures) are inherently non-additive across the date dimension and possibly other dimensions. In these cases, the measure may be aggregated usefully across time, for example, by averaging over the number of time periods.
The Constraint option is used for semi-additive values so that business users will be prompted if they try to create a report with incompatible values. Use constraints to define how the aggregation is to be applied if the field is semi-additive.
An example of where this function is useful is shown below:
| Month | Name | Head Count |
|---|---|---|
| June | Fred | 1 |
| June | Jane | 1 |
| June | Mary | 1 |
| July | Fred | 1 |
| July | Jane | 1 |
| 5 | Sum |
Given the above data, to sum the Head Count alone would result in 5 if Month were not included in the report. This would be misleading for a user (since 5 people were never employed at one time). If you put a constraint rule on Month that it is a mandatory field when Head Count is being summed, then this would result in the following data:
| Month | Head Count |
|---|---|
| June | 3 |
| July | 2 |
| 5 | Sum |
As you can see from these results the report is more meaningful and correct. By applying a constraint to the aggregation of headcount the correct usage of the attribute is ensured by the end user in their reports.
ROLAP is an alternative to the MOLAP (Multidimensional OLAP) technology. While both ROLAP and MOLAP analytic tools are designed to allow analysis of data through the use of a multidimensional data model, ROLAP differs significantly in that it does not require the pre-computation and storage of information.
In v7.2 we are looking at offering more tools that allow users to sum, average, and trend data. See release notes and change log for more details.