Application Of Data Warehouse And Data Mining In Labour Resource Management

With E-business and E-government growing, a mass of data are produced, managed and saved in database or DW (Data Warehouse). How to make good use of the data and enlarge its service to business and government services are important direction of research. DW, OLAP (Online Analytical Processing) and DM (Data Mining) develop rapidly with this application. DW is made up of data drawing out, Data Cleaning and data transformation. It can manage great database effectively. OLAP can create cubes data set base on database or DW. Drawing out and analyzing data with the techniques such as Rotate, Slice, Dice and Drilling. It can afford valuable data to the data user. On the other hand, DM can exploration and uncover meaningful patterns and rules from data with some mining algorithms such as Clustering, Decision Trees, Association Rules and so on.This paper is studied basing on Guangdong Labour Market Information System and use Microsoft SQL Server 2000 as the development platform. With these new techniques, problem of analyzing Xinhui labour mark data is resolved and find out some labour source Structure and distributing rules. The statistics and information can help some departments and decision-makers to draw out some decisions. This paper is organized in five parts.①Something about DW, OLAP and DM are discussed. Some classical clustering algorithms and decision trees algorithms are analyzed and compared.②A Labour Source DW is created with DW techniques. It can manage the labour mark data effectively.③An OLAP Cube data set is created with OLAP techniques base on the Labour Source DW. Some complex problems are solved in some combinatorial conditions. And then, some statistics figs and tables are show. These operations are very simple and the results can be understood easily.④Some Microsoft Clustering Algorithm and MDT Data Mining Models are created base on relational database and OLAP database. Many comparison experiments are conducted and show the validities and capabilities in the data mining algorithms.⑤A decision support system of Labour and Social Security is designed and realized. DW, OLAP and DM techniques are made good use in this system. Great data of Labour and Social Security is managed and analyzed effectively. Valuable information of decision support is created.