Quantitative analysis of data warehouse design quality

M. Pighin, Lucio Ieronutti
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引用次数: 2

Abstract

Information systems allow companies to collect a large number of operational and transactional data. Data warehouses are increasingly used by organisations to extract concise information supporting decision processes. However, data warehouse design strategies as well as the structure and content of the original database largely influence the effectiveness of such tools. Our research is focused on data-driven approaches, and in this paper, we present a solution that, based on a set of metrics measuring different characteristics of the original data sources, effectively supports the creation of data warehouses. Moreover, combining the indexes computed by our metrics on selected dimensions and measures, it is also possible to derive quantitative information on the design quality of the final data warehouse. To demonstrate the effectiveness of our solution, we briefly present the results obtained from the analysis of a selling data warehouse derived from a real-word ERP system.
数据仓库设计质量的定量分析
信息系统使公司能够收集大量的运营和交易数据。组织越来越多地使用数据仓库来提取支持决策过程的简明信息。然而,数据仓库设计策略以及原始数据库的结构和内容在很大程度上影响了这些工具的有效性。我们的研究重点是数据驱动的方法,在本文中,我们提出了一个解决方案,该解决方案基于一组度量原始数据源的不同特征的度量,有效地支持数据仓库的创建。此外,结合我们的度量在选定的维度和度量上计算的索引,还可以获得关于最终数据仓库设计质量的定量信息。为了证明我们的解决方案的有效性,我们简要地介绍了从一个真实的ERP系统中获得的销售数据仓库的分析结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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