| With the rapid development of e-commerce industry and business, lots of e-commerce platforms have emerged, including fertilizer e-commerce platforms and systems. However, current fertilizer e-commerce systems are encounting problems caused by complex data. Traditional technologies of database storage and display which use graphs, charts or reports, have been difficult to meet customer requirements of data visualization and data mining in the era of big data, where data have characteristics of massive and multi-dimensional. Meanwhile, it is difficult for decision makers to make efficient decisions. To solve these problems, in this thesis, we focused on the characteristics of the fertilizer e-commerce system data, based on SSM frame-based data visualization, researched fertilizer e-commerce system data visualization system solutions in the era of big data.Firstly, base on the needs of fertilizer e-commerce visualization system, we investigate the existing data visualization techniques, including a variety of data Google Chart, D3, Processing, R and AmCharts and some other visualization tools, and on then we choose SSM frame-based data visualization technologies to research and development the system.Secondly, we do the system analysis of the fertilizer e-commerce system. We design primary modules of the system, including multi-dimensional analysis reports, pivottable, statistics, promotions management and other module. Then, we use StarUML method for the modeling of the overall functions and process, and we choose to use Spring, Spring MVC and Mybatis mature and stable framework technology and J2EE platform technology to design and to develop the overall system.Thirdly, we test the function test and performance test of the system. We analyse the test results, which have proved that our solutions can meet the overall needs of customers. Fertilizer salesman are freed from the original "quote receivables, billing finding the car" and now can more focus more on investment in agricultural services, publicity and promotion work than before. Customer service efficiency and customer satisfaction have been improved. Continuous compression system helps to link, to reduce product costs, and to improve service quality. Compare with the previous system, our system is more intuitive, more efficient in data queries and more robust.Finally, we conclude and summarize the future work. |
