Analysis of Data Warehouse Architectures: Modeling and Classification

被引:2
|
作者
Yang, Qishan [1 ]
Ge, Mouzhi [2 ]
Helfert, Markus [1 ]
机构
[1] Dublin City Univ, Insight Ctr Data Analyt, Dublin, Ireland
[2] Masaryk Univ, Fac Informat, Brno, Czech Republic
基金
爱尔兰科学基金会;
关键词
Data Warehouse; Architecture; Classification; Modeling; Big Data; Archimate;
D O I
10.5220/0007728006040611
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 representative DWHAs 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.
引用
收藏
页码:604 / 611
页数:8
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