基于数据应用场景的数据资产管理体系构建研究  

Research on the Construction of Data Asset Management System Based on Data Application Scenario

作　　者：吴永欢 宋强 杜舒明 徐炫东 黄绍铭 Wu Yonghuan;Song Qiang;Du Shuming;Xu Xuandong;Huang Shaoming(Guangzhou Power Supply Bureau Co.,Ltd.,Guangzhou 510000,Guangdong;information center of Guangzhou Power Supply Bureau Co.,Ltd;Puyuan Information Technology Co.,Ltd.)

机构地区：[1]广州供电局有限公司,广东广州510000 [2]广州供电局有限公司信息中心 [3]普元信息技术股份有限公司

出　　处：《现代科学仪器》2022年第3期25-29,共5页Modern Scientific Instruments

摘　　要：为了提高数据资产管理的可靠性,扩大数据资源调度能力,提出基于数据应用场景的数据资产管理体系研究。结合在线融合和资源调度方法,构建资产管理大数据融合模型,设计数据应用场景下数据资产的分布结构;采用模糊综合演化聚类分析方法,融合资产管理大数据;通过分析不同应用场景下的资产属性,提取数据资产管理特征;采用样本回归分析方法,进行资产管理的特征匹配和自适应调度,优化资产管理体系。仿真实验结果表明,采用该方法聚类分析大数据,聚类后的特征量具有统一的属性,信息融合度水平较高;采用该方法管理资产数据的可靠性水平达到了90%以上,资源调度能力较强。In order to improve the reliability of data asset management and expand the data resource scheduling ability,the data asset management system based on data application scenario is proposed.Combined with online integration and resource scheduling methods,construct asset management big data fusion model,design the distribution structure of data assets under data application scenarios,adopt fuzzy integrated evolution clustering analysis,integrate big data,manage asset data by analyzing asset attributes in different application scenarios,extract data asset management characteristics;adopt sample regression analysis method,manage feature matching and adaptive scheduling,and optimize the asset management system.Simulation experiment results show that analyzing big data with the clustering method has unified attribute and high information fusion level;the reliability level of managing asset data has reached over 90%and strong resource scheduling ability.

关 键 词：应用场景 数据资产管理 自适应调度模型 信息融合 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]