OLAP And Decision Analysis On Data Of The General MIS

With the rapid development of national information construction, management information systems (MIS) are used widely in all industries. These organizations and corporations can implement the scientific electro-management by using database management systems to collect data and process them. These measures can solve many questions effectively in the processes of production and distribution and storage. Although the MIS is applied rapidly, we find that most of the management information systems exist the comparability largely. Also, once the MIS that is developed for the special application has been put in practice, the change is very difficult. Especially the adjustment to the structure of database will cost larger. So, the reusability of the MIS is the biggest problem that faces to the software users and developers. Along with the increasing of information quantity and complexity, the management system that based on the database technology couldn't satisfy people. In the 1970s, the DSS comes forth. Now, the decision support system has improved greatly. It is developed from the MIS. DSS can offer advanced query and analysis and is capable of secondary support and solving the half-structured and non-structured problem. This dissertation proposes a MIS platform based on database structure reusing to fit the requirement of MIS reusability. We customize the highway construct managing system base on this platform. The system is used for the operational system of highway construct managing department, the communication committee, Chongqing. At present, the system has been used for a period of time and can accomplish the daily information process, but it has many scarcities in the analysis, forecasts and the decisions. By importing the technologies of data warehouse and DSS tools after analysing this highway construct managing system, we build data warehouse with the four themes using the theory and implement technology of data warehouse. Using the data transformation services, we can input and output the data and schedule automatically. At the process of transformation, we can identify, wash, and transform the data. After the analysis to the MDX query technology and OLAP dimensional analysis approach, we can make decisions and analysis aiming at the data in the data warehouse. At last, we can build the data-driven DSS. We can show our results using the PivotTable Services. To the complex analysis, we will develop the special applications. The dissertation discusses such key techniques in the implement exhaustively as the extraction of data, the design of dimensional data cube, data maintenance and renovator and dimensional analysis. We will study them carefully and employ them in the decision support system. The conclusion verifies that the result of analysis can give powerful support to managers'decisions.