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Empirical validation of metrics for object oriented multidimensional model for data warehouse

机译:面向数据仓库的面向对象多维模型的指标的经验验证

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摘要

Metrics have been popularly used to guide designers to develop quality data models. Researchers have proposed metrics for multidimensional models for data warehouses. These metrics need to be empirically validated to prove their practical utility. This paper presents the empirical validation of the metrics for multidimensional models for data warehouses at conceptual level. Quality attributes namely, understandability and efficiency are evaluated through various combinations of metrics. Multiple linear regression analysis has been used in this paper for predicting the multidimensional models quality. The results show that these metrics may be considered as solid indicators for quality of multidimensional data models. Finally, accuracy of our models in predicting the multidimensional models' quality is evaluated.
机译:度量标准已广泛用于指导设计师开发高质量的数据模型。研究人员已经为数据仓库的多维模型提出了度量标准。这些指标需要进行经验验证,以证明其实用性。本文从概念上介绍了数据仓库多维模型的指标的经验验证。通过各种指标组合来评估质量属性,即可理解性和效率。本文使用多元线性回归分析来预测多维模型的质量。结果表明,这些指标可被视为多维数据模型质量的可靠指标。最后,评估了我们的模型在预测多维模型质量方面的准确性。

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