A perennial challenge faced by many organizations is the management of their increasingly large multidimensional databases (MDB) that can contain millions of data instances. The problem is exacerbated by the diversity of the users’ specific needs. Personalization of MDB content according to how well they match user’s preferences becomes an effective approach to make the right information available to the right user under the right analysis context. In this paper, we propose a framework called OLAP Content Personalization (OCP) thataims at deriving a personalized content of a MDB based on user preferences. At query time, the system enhances the query with related user preferences in order to simulate its performance upon an individual content. We discuss results of experimentation with a prototype for content personalization.