Part of the book series:Advances in Intelligent and Soft Computing ((AINSC,volume 124))
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Abstract
Real-time data warehouse as an extension of traditional data warehouse, it is effectively shortening the delay of information and providing timely and accurate decision support to decision makers. The ETL processing is the core technology of data warehouse, especially in real-time data warehouse. This paper is analyzing the current mainstream technology for real-time ETL. We propose a way to capture changed data which is based on log analysis and log listening. This method provides an effective solution for the huge amount of data, which greatly improve system performance.
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Authors and Affiliations
Department of Computer, College of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China
Haihe Zhou & Yang Xu
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Dingyu Yang
- Haihe Zhou
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- Dingyu Yang
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- Yang Xu
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Editors and Affiliations
Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, 200240, Shanghai, China
Yinglin Wang
School of Information Science and Technology, Southwest Jiaotong University, 610031, Chengdu, Sichuan Province, China
Tianrui Li
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© 2011 Springer-Verlag Berlin Heidelberg
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Zhou, H., Yang, D., Xu, Y. (2011). An ETL Strategy for Real-Time Data Warehouse. In: Wang, Y., Li, T. (eds) Practical Applications of Intelligent Systems. Advances in Intelligent and Soft Computing, vol 124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25658-5_41
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