Authors:
Emiel Caron
1
and
Hennie Daniels
2
Affiliations:
1
Erasmus University Rotterdam, Netherlands
;
2
Tilburg University, Netherlands
Keyword(s):
Business Intelligence, Multi-dimensional databases, OLAP, Sensitivity analysis, Explanation, Data mining.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Data Warehouses and OLAP
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
Today's multi-dimensional business or OnLine Analytical Processing (OLAP) databases have little support for sensitivity analysis. Sensitivity analysis is the analysis of how the variation in the output of a mathematical model can be apportioned, qualitatively or quantitatively, to different sources of variation in the input of the model. This functionality would give the OLAP analyst the possibility to play with ``What if...?''-questions in an OLAP cube. For example, with questions of the form: ``What happens to an aggregated value in the dimension hierarchy if I change the value of this data cell by so much?'' These types of questions are, for example, important for managers that want to analyse the effect of changes in sales, cost, etc., on a product's profitability in an OLAP sales cube. In this paper, we describe an extension to the OnLine Analytical Processing (OLAP) framework for business analysis in the form of sensitivity analysis.