基于Vensim PLE的决策监管类系统的数据质量影响因素分析——以智能化国资国企在线监管平台系统为例  

Analysis of data quality influencing factors of decision-making and supervisionsystem based on Vensim PLE——Take the online supervision platformsystem of state-owned assets and enterprises as an example

作　　者：孔雁 曹子傲 Kong Yan;Cao Ziao(School of Management,Zhengzhou University,Zhengzhou 450000,China)

机构地区：[1]郑州大学管理学院,河南郑州450000

出　　处：《网络安全与数据治理》2024年第11期64-69,共6页CYBER SECURITY AND DATA GOVERNANCE

摘　　要：大数据时代,数据赋能和应用给政府和国有企业的决策和监管带来了便利,但决策监管类系统面临源数据获取、分析、处理等过程导致的数据质量不高问题,影响决策的精准性和监管的有效性。结合本人参与该平台建设需求分析和数据获取的实际工作过程,针对国有资产和国有企业数据获取到应用过程中影响数据质量的主要因素进行分析,构建了数据质量模型的因果关系图和流图,并通过Vensim PLE进行仿真实验,识别到人才对数据质量的重要性。同时,了解其中的学习培训时间、需求变更和元数据因素对数据质量的具体影响趋势,并提出对应改进数据质量的有效方法。In the era of big data,data empowerment and application have brought convenience to the decision-making and supervision of governments and state-owned enterprises.However,the decision-making and supervision system faces the problem of low data quality caused by the process of source data acquisition,analysis and processing,which affects the accuracy of decision-making and the effectiveness of supervision.This paper mainly combines the specific practice of demand analysis and data acquisition in the construction process of intelligent state-owned enterprises online supervision platform,analyzes the main factors affecting data quality in the process of supervisory platform from data acquisition to application,and constructs the causality diagram and flow diagram of data quality model.Simulation experiments are conducted through Vensim PLE to identify the importance of talent and leadership participation in platform system construction on data quality,understand the specific influence trends of learning and training time,demand changes and source data factors,and put forward effective methods to improve data quality.

关 键 词：数据质量 决策监管系统 系统动力学 Vensim PLE 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] TP311.5[自动化与计算机技术—计算机科学与技术]