In the traditional data warehouse modeling, a numerical attribute with continuous data are not suitable for modeling as a dimension, unless it is partitioned into a concept hierarchy according to some predefined mapping-rules. In some cases, such rules are flexible or unavailable, so the partitioned dimension is proposed in this paper as the solution of modeling the numerical dimension in these cases. Partitioned dimension is generated by clustering the frequent query conditions. The query and dynamic OLAP operations over partitioned dimensions are also introduced. At last, some experiments show that the proposed modeling approach is effective and efficient.