Continuous Data Warehouse: Concepts, Challenges and Potentials

The multidimensional structures or hypercubes are commonly used in OLAP (On Line Analytical Processing) to store and organize the data with the goal of optimizing query response time. The multidimensional approach is based on the concept of facts or measures analyzed with respect to various prospects or dimensions to facilitate the decision making process. Dimensions can be seen as axis of analysis, forming a vector space in which each cell is located by a set of coordinates. In the conventional multidimensional structures dimensions have discrete values and are organized in different levels of hierarchies. However, when dealing with the analysis of natural phenomena like meteorology or pollution the discrete structures show some shortcomings. Our goal is to introduce mechanisms, based on interpolation, to the spatial and temporal dimensions which will give the user the impression of navigating in a continuous hypercube even though it is discrete. Having continuous dimensions enables users to navigate in the hypercube in totally different ways. In this paper we go over some of the concepts and research issues associated with continuous multidimensional structures and we list some of their potentials.