数据流通交易场景下数据质量综合管理体系与技术框架研究

Comprehensive Management System and Technical Framework of Data Quality in the Data Circulation Transaction Scenario

【目的】在数据交易特定场景下,为加强数据流通管理,完善数据流通交易规则,针对数据产品质量评估及管理关注的侧重点,构建一套数据流通交易场景下数据质量综合管理体系与技术框架。【方法】运用文献调研法梳理国内外数据质量评估现状与数据质量检核常用手段,结合业界经验与数据交易的具体场景,从原始数据集、脱敏数据集、模型化数据和AI化数据4类数据产品出发,提出数据交易流通中场景的质量评估模型,并提出针对场景及业务需求提升数据交易前、交易中和交易后各环节数据质量的管理体系。【结果】明确以"6543"即六大指标、五类主体、四类产品及三大评估方法为架构的数据交易流通质量评估模型,并为交易前、交易中和交易后对数据产品的规范性、完整性、准确性、一致性、时效性和可访问性的检测和优化提供支撑。【局限】尚未在真实交易场景中对数据质量模型与管理体系进行系统性使用,框架设计缺乏实践检验。【结论】提出的质量评估模型与质量管理体系为实现数据交易全过程中数据产品的质量评估与提升具有重要作用。

[Objective]In the context of data transaction,in order to strengthen data circulation management and improve data circulation transaction rules,a set of comprehensive data quality management system and technical framework under the scenario of data circulation transaction are constructed according to the focus of data product quality evaluation and management.[Methods]Using literature research method,we reviewed the current literature of data quality assessment and commonly used methods of data quality inspection at home and abroad.Combining industry experience and specific scenarios of data transactions,we proposed a quality evaluation model containing raw data sets,desensitized data sets,modeled data,and AI-based data,along with a management system to improve the data quality before,during,and after data transactions.[Results]This paper raises a data quality evaluation model in transaction context that based on the“6543”structure,namely six types of main indicators,five types of subjects,four types of products,and three types of evaluation methods.Provide testing and optimization solutions to data normativeness and completeness in the pre-transaction phase,data accuracy and consistency during the transaction phase,as well as data timeliness and accessibility in post-transaction phase.[Limitations]The data quality model and management system have not been systematically used in real transaction scenarios,and there is a lack of actual testing.[Conclusions]The proposed quality evaluation model and quality management system play an important role in realizing the quality evaluation and improvement of data products in the whole process of data transaction.