This paper explores the importance of semantic integrity during data warehouse design and its impact on the successful use of the implemented warehouse. This was achieved through a case study. A conceptual framework for describing intersubjective meaning in data modelling has been developed to provide a theoretical basis for explaining how a data model is interpreted through the meaning levels of understanding, connotation and generation, and also how a data model is created from an existing meaning structure by intention, generation and action. This paper also describes inhibiting factors for understanding the physical data model based on the case study findings. Strategies are suggested to address the factors inhibiting the generation of meaning from a data model. The result of the exploration is the recognition that the implementation of a data warehouse may not assist with providing a detailed understanding of the semantic content of the data warehouse.