Occupational Health Olap Analysis System Based On Data Warehouse Design And Implementation,

Objectives:1. To master the dataware and OLAP technology-related theories and methods; 2. To master the occupational health information systems and its current data information; 3. To explore the design and implementation methods of the OLAP analysis system on base of the occupational health dataware as well as the applied effects of the system; 4. To explore the analytical methods of occupational health information system which is aimed at providing basis for the promotion of other public health-related technologies.Methods:1. To obtain the theories and applied methods of relevant health sectors,computer sciences,associated software function modules and its application status by literature review method; 2. To obtain the construction status on occupational health information system and application of occupational health data by literature review method; 3. To conduct systematic analysis by object-oriented software design methods including user-needs analysis, requirements analysis, network topology, technology architecture, system architecture, data architecture.Results:The research project has utilized the OLAP technology to complete the analysis of occupational health dataware based on the research fruits of development theory,technology,components,implementation of occupational health database, and developed an analytic system for occupational health database.Conclusion:The application of dataware and OLAP technologies in the occupational health information system is convenient and effective for professionals to display,understand and manipulate multi-dimensional data sets.Suggestions:The occupational health system could be further improved in the modeling viewpoint,the design of dimension,selection of measurement and pre-analytic function so as to give professionals a better understanding on occupational health. The data analytic methods have improved the effectiveness of occupational health data in terms of the function of data decision analysis, thus it will offer better information for health professionals and decision-makers.