Student Employment Management System Based On Data Warehouse

As computer being wildly used and upgraded, the data mining growing into a new rising and multi-disciplinary application field, are playing more and more important role in the information analysis of decision support system.Association mining is an important research branch of the data mining, and it aims at discovering the relationship among items in a data set. The data mining is the main measure of deriving knowledge from large databases. Because of its simple form and it can be easily understood, association mining has been successfully applied to many fields. It not only can test the knowledge modes exiting in the industry, but also can find some new rules hidden.As education innovation in China being enhanced, higher vocational education in has been significantly developed. At present, in all kinds of schools, especially in vocational education at all levels of schools, the school database has been well constructed and has stored enormous education and teaching information. According to some researches, the historical data with a large number of educational information of historical data has not been well used or dig the education rules hidden in the database out. Consequently, the majors of a number of vocational education schools have little distinction, and the course schedules have no clear distinction. Graduates are hard to find suitable job according with their education experience. To analyze the reasons, besides current curriculum can not be kept up with the actual employer's requirement, there are also many hidden reasons, which result in lackness of students'ability after three to five-year education. However, some competent students have been constrained by majors or some undiscovered factors. The purpose of this article is to dig out correct, reliable and credible correlative rules from a large amount of vocational education information.Though data collection, data arrangement, research and analysis, this thesis carries out the data mining of historical education data of current vocational school. The purpose is: (1) to find out the rules from the data to verify whether current students'economic status of households and majors in school can affect students'employment. (2) Through the study of this topic, select the appropriate mining algorithm, the appropriate data mining tools and software to create a viable data mining rules of major in school, family economic status and employment data, which can be widely applied on vocational education for decision making and research. (3) Though correlation of the major in school, family economic status, regional distribution and employment discovered by data mining, this article can properly lead the students to choose their majors in school and finally improve their employment rate.Based on student data from Sichuan college of Architectural technology since 2006, data warehouse, OLAP technology and data mining, This thesis analyzes vocational school graduates'employment data. Through student's major, student's location, education experience and employed time, on-line analysis and data mining has been carried out to find out that internal reason of employment status of the student from different aspects and different levels and discover major arrangement requirements from the students, which could offer a decision-making support for course design and education method.