摘要
数据资产的积累和清理重在围绕研发端、质量工艺端、制造端、客户体验端等应用场景去展开,立足大数据应用需要专注物联网细分行业数据的共性和融合性,在海量数据分析方式上,用标准化的流程实现流水线一样的大数据平台开发模式,适当差异化考虑,以全面提升分析效率,架设更强大灵活的维护通道和升级换代在线服务,需要保持历史数据安全,不能因为系统问题而丢失。
The accumulation and cleaning of data assets focus on the application scenarios of R & D, quality process,manufacturing, customer experience, etc. Based on big data application, we need to focus on the commonness and integration of the data in the Internet of things subdivision industry. In the way of mass data analysis, we should use standardized process to realize pipelined big data platform development mode, consider the appropriate differentiation, in order to improve the efficiency of analysis.The installation of more powerful and flexible maintenance channels and upgraded online services requires the preservation of historical data security and cannot be lost because of system problems.
出处
《衡器》
2018年第12期5-6,共2页
Weighing Instrument
关键词
大数据
应用场景
分析效率
在线服务
数据安全
big data
application scene
analysis efficiency
online service
data security
