OLAP defines a set of data warehousing query tools characterized by providing a multidimensional view of data. Information can be shown at different aggregation levels (often called granularities) for each dimension. In this paper, we try to outline the benefits of understanding the relationships between those aggregation levels as PartWhole relationships, and how it helps to address some semantic problems. Moreover, we propose the usage of other Object-Oriented constructs to keep as much semantics as possible in analysis dimensions. Key Words: Multidimensional modeling, Analysis dimensions, Mereology, Object-Oriented modeling, On-Line Analytical Processing