Paper
13 April 2009 Design of data warehouse in teaching state based on OLAP and data mining
Lijuan Zhou, Minhua Wu, Shuang Li
Author Affiliations +
Abstract
The data warehouse and the data mining technology is one of information technology research hot topics. At present the data warehouse and the data mining technology in aspects and so on commercial, financial industry as well as enterprise's production, market marketing obtained the widespread application, but is relatively less in educational fields' application. Over the years, the teaching and management have been accumulating large amounts of data in colleges and universities, while the data can not be effectively used, in the light of social needs of the university development and the current status of data management, the establishment of data warehouse in university state, the better use of existing data, and on the basis dealing with a higher level of disposal --data mining are particularly important. In this paper, starting from the decision-making needs design data warehouse structure of university teaching state, and then through the design structure and data extraction, loading, conversion create a data warehouse model, finally make use of association rule mining algorithm for data mining, to get effective results applied in practice. Based on the data analysis and mining, get a lot of valuable information, which can be used to guide teaching management, thereby improving the quality of teaching and promoting teaching devotion in universities and enhancing teaching infrastructure. At the same time it can provide detailed, multi-dimensional information for universities assessment and higher education research.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lijuan Zhou, Minhua Wu, and Shuang Li "Design of data warehouse in teaching state based on OLAP and data mining", Proc. SPIE 7344, Data Mining, Intrusion Detection, Information Security and Assurance, and Data Networks Security 2009, 73440M (13 April 2009); https://doi.org/10.1117/12.816443
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KEYWORDS
Data mining

Data modeling

Mining

Data conversion

Databases

Data centers

Structural design

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