智能多维建模

Swati Hira, P. Deshpande
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引用次数: 1

摘要

联机分析处理(OLAP)系统大大简化了分析业务数据的过程,并已在工业中得到广泛应用。这类系统主要使用多维数据模型来构建其数据。然而,当前的多维数据模型在时间和技能上都不够,无法对某些实际应用程序领域中的复杂数据进行建模。多维数据分析是基于度量、维度和层次的。手动查找它们的过程非常关键且耗时,因为涉及多个地区、产品和员工的大型复杂数据。本文提出了一种智能多维建模系统,它可以帮助建模者建立多维模型,并通过隐藏物理数据库的异构性提供逻辑层面的工作。本文提出了识别度量、维度和层次的过程,以生成多维模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Multidimensional Modelling
On-Line Analytical Processing (OLAP) systems considerably ease the process of analyzing business data and have become widely used in industry. Such systems primarily employ multidimensional data models to structure their data. However, current multidimensional data models fall short in time and skills to model the complex data found in some real-world application domains. Multidimensional data Analysis is based on Measure, Dimensions and Hierarchies. Process to find them manually is very crucial and time consuming because large and complex data is involved across multiple regions, products, and employees. This paper presents an Intelligent Multidimensional modelling system which helps the modeller in building multidimensional model and provides working at logical level by hiding heterogeneousity of physical database. The paper proposes the process to identify Measures, Dimensions, and Hierarchies to generate multidimensional model.
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