For much of the last decade, conventional theories surrounding decision support architectures have focused more on cost than business benefit. Lack of return-on-investment (ROI) quantification has resulted in platform selection criteria being focused on perceived minimization of initial system cost rather than on maximizing lasting value to the enterprise. Often these decisions are made within departmental boundaries without consideration of an overarching data warehousing strategy.
This reasoning has led many organizations down the path of data mart proliferation. This represents the creation of nonintegrated data sets developed to address specific application needs, usually with an inflexible design. In the vast majority of cases, data mart proliferation is not the result of a chosen architectural strategy, but a consequence due to the lack of an architectural strategy.
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