Hierarchies are important structures in a data warehouse, because they offer several levels of precision on the analytical view of warehoused data. Most of actual methodologies for hierarchy building with data mining algorithms don't take account the multidimensional context of the modified dimension. Therefore, in this paper, we present an algorithm enriching a dimension with factuel data. This algorithm has been implemented on a ROLAP architecture.