基于大数据的智能企业管理系统设计
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摘要
传统在网络环境下构建的企业管理系统,对企业管理中的大数据分析效果差,无法提高企业经营管理效率。设计基于大数据的智能企业管理系统,采用管理应用创新模块,通过多屏互动等方式实现企业智能管理应用创新,利用大数据处理模块对数据进行采集、传输、存储等处理。系统软件采用三层式架构设计数据整理流程,消除关联信息;通过数据清洗过程排除冗余信息;采用基于大数据行为模型的故障预测方法分析时间序列,实现系统故障预判。实验结果表明,系统测试的预期结果与实际结果一致,系统最高吞吐量为290 000 Mb/s、平均响应时间为3.5 s,说明所设计系统可实现高效率的智能企业管理。
Since the traditional enterprise management system built in the network environment has a poor effect on big da-ta analysis in enterprise management and cannot improve the efficiency of enterprise operation and management,an intelligent enterprise management system based on big data is designed. The management and application innovation module is adopted to realize enterprise intelligent management and application innovation by means of multi-screen interaction and other modes. The big data processing module is used to collect,transmit and store data. The three-layer architecture is used for the system soft-ware to design the data compilation process,so as to eliminate related information. The redundant information is eliminated us-ing the data cleaning process. The fault prediction method based on the big data behavior model is used to analyze time series,so as to realize fault pre-judgment of the system. The experimental results show that the expected results of the system test are consistent with the actual results,the maximum throughput of the system is 290 000 Mb/s,and its average response time is 3.5 s,which indicates that the designed system can achieve efficient intelligent management of enterprises.
Since the traditional enterprise management system built in the network environment has a poor effect on big da-ta analysis in enterprise management and cannot improve the efficiency of enterprise operation and management,an intelligent enterprise management system based on big data is designed. The management and application innovation module is adopted to realize enterprise intelligent management and application innovation by means of multi-screen interaction and other modes. The big data processing module is used to collect,transmit and store data. The three-layer architecture is used for the system soft-ware to design the data compilation process,so as to eliminate related information. The redundant information is eliminated us-ing the data cleaning process. The fault prediction method based on the big data behavior model is used to analyze time series,so as to realize fault pre-judgment of the system. The experimental results show that the expected results of the system test are consistent with the actual results,the maximum throughput of the system is 290 000 Mb/s,and its average response time is 3.5 s,which indicates that the designed system can achieve efficient intelligent management of enterprises.
引文
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