Data Warehouse Modeling and Quality Issues

Abstract

Data warehouses can be defined as `subject-oriented', integrated, time-varying, non-volatile collections of data that is used primarily in organizational decision making. Nowadays, data warehousing became an important strategy to integrate heterogeneous information sources in organizations, and to enable On-Line Analytic Processing (OLAP). Unfortunately, neither the accumulation, nor the storage process, seem to be completely credible. For example, it has been suggested in the literature that more than $2 billion of U.S. federal loan money have been lost because of poor data quality at a single agency, that manufacturing companies spent over 25% of their sales on wasteful practices, a number which came up to 40% for service companies. The question that arises, then, is how to organize the design, administration and evolution choices in such a way that all the different, and sometimes opposing, quality user requirements can be simultaneously satisfied. To tackle this problem, ...

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