Coupling OLAP and data mining for prediction
Najlae Korikache, Amina Yahia · International Journal of Computing and Optimization · 2014
Copyright © 2014 Najlae KORIKACHE and Amina YAHIA. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The cooperation of transactional databases and decision making systems resulted in warehouse concepts, multidimensional data bases (cube) and OLAP system. These concepts aim to implement effective solutions for the management and interactive analysis of large volumes of data and provide decision-making process. Integrating the prediction in OLAP environment is a topic that is experiencing a growing interest which opens several research paths. This contribution addresses the problem of predicting from a data cube and consists of partitioning the original cube into dense sub-cubes as well as building and validating for each dense sub-cube a prediction model. It also consists of choosing (by the user) the cell to predict rather than the context of analysis and determining the sub-cube which contains the designated cell by the user and then predict the value of the cell through the prediction model of the sub-cube.