DataBase as a Service (DBaaS) providers need to improve their existing capabilities in data management and balance the efficient usage of virtual resources to multi-users with varying needs. However, there is still no existing method that concerns both with the optimization of the total ownership price and the performance of the queries of a Cloud data warehouse by taking into account the alternative virtual resource allocation and query execution plans. Our proposed method tunes the virtual resources of a Cloud to a data warehouse system, whereas most of the previous studies used to tune the database/queries to a given static resource setting. We solve this important problem with an exact Branch and Bound algorithm and a robust Multiobjective Genetic Algorithm. Finally, through several experiments we conclude remarkable findings of the algorithms we propose.