« Data Warehouse is not only for analytics | Main | Assess Data Warehouse Project Readiness »
April 2, 2008
Non-Additive Measures in OLAP
Additivity and correct aggregation methods application is fundamental to the success of Business Intelligence. The most common mistakes the modelers and designers make is on - Setting the Right Hierarchies AND Establishing Right Additivity and aggregation rules. You need to go through the chapter of business dimensional hierarchies, before you go through this chapter. Additivity of a measure is when you are able to apply the sum operator across all the dimensions. Other aggregations on measures-facts are when you use operators like Average, Maximum and Minimum. The topics in this chapter are focused on the areas which have additivity or aggregation constraints. For measures, which do not fall into these constraints are considered Additive.
The non-additive measures are:
- Ratios & Percentages
- Intensity Measures (like temperature)
- Grades
- Averages/Maximums/Minimums
The Semi-Additive Measures(Where additivity is over certain dimensions and not on all dimensions):
- Dirty Data
- Historical Data
- Category Data
- Periodic Snap-shots
The details on this subject can be seen on Additivity of Measures
Posted by Rajan Gupta at April 2, 2008 2:30 AM
