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@inproceedings{1495036, author = {Qishan, Yang and Ge, Mouzhi and Helfert, Markus}, address = {Crete, Greece}, booktitle = {Proceedings of the 21st International Conference on Enterprise Information Systems}, doi = {http://dx.doi.org/10.5220/0007728006040611}, keywords = {Data Warehouse; Architecture; Classification; Modeling; Big Data; Archimate}, howpublished = {tištěná verze "print"}, language = {eng}, location = {Crete, Greece}, isbn = {978-989-758-372-8}, pages = {604-611}, publisher = {SciTePress}, title = {Analysis of Data Warehouse Architectures: Modeling and Classification}, year = {2019} }
TY - JOUR ID - 1495036 AU - Qishan, Yang - Ge, Mouzhi - Helfert, Markus PY - 2019 TI - Analysis of Data Warehouse Architectures: Modeling and Classification PB - SciTePress CY - Crete, Greece SN - 9789897583728 KW - Data Warehouse KW - Architecture KW - Classification KW - Modeling KW - Big Data KW - Archimate N2 - 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. ER -
QISHAN, Yang, Mouzhi GE a Markus HELFERT. Analysis of Data Warehouse Architectures: Modeling and Classification. In \textit{Proceedings of the 21st International Conference on Enterprise Information Systems}. Crete, Greece: SciTePress, 2019, s.~604-611. ISBN~978-989-758-372-8. Dostupné z: https://dx.doi.org/10.5220/0007728006040611.
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