摘要
在电力客户服务、电动汽车、综合能源、设备健康状态评估等业务领域,海量数据无法被业务人员直观理解,基础数据不能全面地支撑公司精益化管理和精准化服务。本文采用将电力数据标签化的方法,设计客户、设备、组织对象、供应商、员工等五类主体标签体系,以不同的目标主体为载体,以业务需求为导向,设计标签规则、开发算法模型、构建标签服务、推荐标签策略,实现了数据标签分类分级、有序管理、精准查询。通过运用“数据标签”,对人、事、物等进行精准刻画,满足公司差异化管理和运营服务的需求,并提供了基于公司两级数据中台实现两级标签协同共享、交互应用的全生命周期建设流程,能够助力于业务应用精准制定策略、快速做出决策,实现业务数据化、数据业务化良性循环。
In business areas such as power customer service,electric vehicles,integrated energy,and equipment health assessment,massive amounts of data cannot be intuitively understood by business personnel,and basic data cannot fully support the company s lean management and precise services.This paper adopts the method of tagging power data,designing five types of subject tag systems,including customers,equipment,organizational objects,suppliers,and employees.Different target subjects are used as carriers,dimension conversion,data calculation,and text mining are used as the ways,and actual business is treated as purposes to do the classification,orderly management,and precise query of data tags generated under different business requirements.By using"data tags",accurate descriptions of people,events,and things are achieved,meeting the company's differentiated management and operation service needs.It also provides a full life cycle construction process based on the company's two-level data middle platform to realize two-level tag collaborative sharing and interactive application,which helps business applications to accurately formulate strategies and quickly make decisions,as well as realize a virtuous circle of business dataization and data commercialization.
作者
郭敏
林晓静
尹泽楠
万凯
GUO Min;LIN Xiaojing;YIN Zenan;WAN Kai(Big Data Center of State Grid Corporation of China,Beijing 100032,China)
出处
《电力大数据》
2020年第10期86-92,共7页
Power Systems and Big Data