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ABSTRACT
The analysis of business data is often an ill-defined task characterized by large amounts of noisy data. Because of this, business data analysis must combine two kinds of intertwined tasks: exploration and analysis. Exploration is the process of finding the appropriate subset of data to analyze, and analysis is the process of measuring the data to provide the business answer. While there are many tools available both for exploration and for analysis, a single tool or set of tools may not provide full support for these intertwined tasks. We report here on a project that set out to understand a specific business data analysis problem and build an environment to support it. The results of this understanding are, first of all, a detailed list of requirements of this task; second, a set of capabilities that meet these requirements; and third, an implemented client-server solution that addresses many of these requirements and identifies others for future work. Our solution incorporates several novel perspectives on data analysis and combines a history mechanism with a graphical, re-usable representation of the analysis and exploration process. Our approach emphasizes using the database itself to represent as many of these functions as possible.
REFERENCES
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CITED BY 6
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