Many data warehouse systems have been developed recently, yet data warehouse practice is not sufficiently sophisticated for practical usage. Most data warehouse systems have some limitations in terms of flexibility, efficiency, and scalability. In particular, the sizes of these data warehouses are forever growing and becoming overloaded with data, a scenario that leads to difficulties in data maintenance and data analysis. This research focuses on data-information integration between data cubes. This research might contribute to the resolution of two concerns: the problem of redundancy and the problem of data cubes’ independent information. This work presents a semantic cube model, which extends object-oriented technology to data warehouses and which enables users to design the generalization relationship between different cubes. In this regard, this work’s objectives are to improve the performance of query integrity and to reduce data duplication in data warehouse. To deal with the handling of increasing data volume in data warehouses, we discovered important inter-relationships that hold among data cubes, that facilitate information integration, and that prevent the loss of data semantics.