Data uncertainty is an inherent property in various applications due to reasons such as measurement errors, incompleteness of data and so on. While On-Line Analytical Processing (OLAP) has been a powerful method for analyzing large data warehouse, OLAP over uncertain data has become a valuable and attractive issue because of the increasingly demand<br>for handling uncertainty in multidimensional data. In this paper, we firstly describe our UStar-Schema model that extends the<br>traditional O
