数据仓库体系结构分析:建模和分类

Qishan Yang, Mouzhi Ge, M. Helfert
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引用次数: 7

摘要

经过几十年的发展和创新,数据仓库及其架构已经扩展到各种环境中的各种衍生产品,以满足不同组织的需求。虽然对数据仓库架构(DWHA)的调查和分类有一些专门的研究,但对DWHA进行系统建模和分类的研究有限。特别是在大数据时代,数据是爆炸性的。越来越多的新兴架构和技术被用来操纵和管理这个领域的大数据。因此,重新审视和研究具有新创新的dwha是有价值的。在本文中,我们收集了116份出版物,并使用Archimate对73个不同的dwha进行了建模,然后确定了9个具有代表性的dwha,并将其总结为一个“大图景”。在此基础上,提出了一种新的分类模型。该模型可以指导研究人员和实践者从组件和架构的角度识别、分析和比较dwha的差异和趋势。
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Analysis of Data Warehouse Architectures: Modeling and Classification
With decades of development and innovation, data warehouses and their architectures have been extended to a variety of derivatives in various environments to achieve different organisations’ requirements. Although there are some ad-hoc studies on data warehouse architecture (DWHA) investigations and classifications, limited research is relevant to systematically model and classify DWHAs. Especially in the big data era, data is generated explosively. More emerging architectures and technologies are leveraged to manipulate and manage big data in this domain. It is therefore valuable to revisit and investigate DWHAs with new innovations. In this paper, we collect 116 publications and model 73 disparate DWHAs using Archimate, then 9 representativeDWHAs are identified and summarised into a ”big picture”. Furthermore, it proposes a new classification model sticking to state-of-the-art DWHAs. This model can guide researchers and practitioners to identify, analyse and compare differences and trends of DWHAs from componental and architectural perspectives.
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