Data for decision-making applications are based on dimensions, such as time, customer, and product. These dimensions are naturally related by hierarchies. Hierarchies are crucial to multidimensional modeling. Defining hierarchies using star or snowflake schemas can be misleading, since they are not explicitly well-modeled. However, deriving them from conceptual UML or ER schemas is a non-trivial task since they have no direct equivalent in conceptual models. This paper focuses on the definition of multidimensional hierarchies. We present and illustrate rules for defining multidimensional hierarchies from UML schemas, especially based on aggregation and generalization hierarchies. The definition of hierarchies is part of a data warehouse design method based on the three usual modeling levels : conceptual, logical, and physical. The conceptual schema is based on the UML notation. The logical schema is represented using a unified pivot multidimensional model. The physical schema depends on the target ROLAP or MOLAP tool.