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Data warehouses are expensive and complicated, requiring the careful integration of numerous major components. The innovations data warehouses were meant to foster are often stalled by the degree of time, cost and policy issues it requires to sustain and enhance them. In addition, the leverage that these investments yield is too low and the data warehouse informs too few people and processes. These two classes of problems, architectural and practical, and their solutions, are the subjects of this paper. This paper also presents a conceptual foundation for an improved approach that is based on model-driven architectures.
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