Analysis of Data Warehouse Architectures: Modeling and Classification

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Authors	QISHAN Yang GE Mouzhi HELFERT Markus
Year of publication	2019
Type	Article in Proceedings
Conference	Proceedings of the 21st International Conference on Enterprise Information Systems
MU Faculty or unit	Faculty of Informatics
Citation
Doi	http://dx.doi.org/10.5220/0007728006040611
Keywords	Data Warehouse; Architecture; Classification; Modeling; Big Data; Archimate
Description	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.