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Multidimensional database technology is a key factor in the interactive analysis of large amounts of data for decision making purposes. In contrast to previous technologies, these databases view data as multidimensional cubes that are particularly well suited for data analysis. Multidimensional models categorize data either as facts with associated numerical measures or as textual dimensions that characterize the facts. Queries aggregate measure values over a range of dimension values to provide results such as total sales per month of a given product. Multidimensional database technology is being applied to distributed data and to new types of data that current technology often cannot adequately analyze. For example, classic techniques such as preaggregation cannot ensure fast query response times when data-such as that obtained from sensors or GPS-equipped moving objects-changes continuously. Multidimensional database technology will increasingly be applied where analysis results are fed directly into other systems, thereby eliminating humans from the loop. When coupled with the need for continuous updates, this context poses stringent performance requirements not met by current technology.
Pedersen et al. (2001) studied this question.