Mining uncertain data warehouse

Real data is pervaded with uncertainty. As a consequence, the development and adaptation of automatic knowledge acquisition techniques under uncertainty is entirely advisable. Among them fuzzy sets theory formulizes and analyses the situations in which the uncertainty is due to the vague (fuzzy) data. Any good decision is based on information. Data Warehousing and Knowledge Discovery technology is emerging as a key technology for enterprises that wish to improve their data analysis, decision support activities, and the automatic extraction of knowledge from data. In this paper, we introduce a novel decision support system for handling uncertain climate data using the data warehousing technology combined with fuzzy sets theory as a mathematical data mining technique in the presence of uncertainty. This novel approach is based on the membership function and multidimensional analysis. From our findings, we conclude that data warehousing and data mining are essentials for an effective decision support system.