The Research On The Information System For The Graduates' Employment Base On Data Warehouse

The major task of a secondary vocational school is to produce students with qualified skills and practical abilities. In the job-hunting process, however, there is a growing tendency that job offers cannot find capable employees while graduates cannot find suitable positions. Therefore, in order to improve students applied skills and their employment rate, priorities must be given to analyze what kind of skilled talents the society needs and factors influencing the students to gain those skills. At present, a number of information management systems are being operated among secondary vocational schools, such as student information management system, teaching affairs information management system, and moral education information management system, etc. However, these systems are simply used to collect and store data with traditional databases. Due to a lack of information awareness and technical platform, administrators only obtain some superficial information through simple statistics and sequencing, while information hidden in the data has not been further analyzed or fully used. Adopting Data Warehouse (DW) to information management of secondary vocational schools for an in-depth analysis of students' data in support of school's decision-making is a worthwhile research project.Making full use of DW concept and OLAP (Online Analysis Procession) technique, the paper analyzes all the data concerning student management accumulated by secondary vocational schools all through the years, identifies key factors influencing students' employment, and finds out the rules regulating students' employment, so as to provide decision-makers with grounds on teaching reform and curriculum setting. Since previous data are mostly stored by means of traditional data bases such as Access and MS Excel etc, this system takes Microsoft SQL Server 2000 as a DW platform, to extract useful data from multiple transaction-processing data bases for efficient management of mass data through data clearing and transformation; then it makes use of OLAP function provided by Analysis Services to build multi-dimensional cube of network models; based on the cube, data are extracted and analyzed with such techniques as rotating, slicing, sectioning, and drilling, in order to find out key factors influencing students' employment. Thus, valuable data information is provided for decision-making.Focusing on the above-mentioned content, major tasks for the author to undertake include: making an in-depth study on DW and OLAP; building multi-dimensional data based on the theme of "students' employment" demanded by decision-makers; analyzing OLAP from various perspectives and designing and establishing ADOMD interface.