摘要
在对国际与国内关于数据质量定义及评价方面研究成果的分析发现,到目前为止,对这些问题的研究仍然存在许多缺陷,如数据质量的定义不统一,数据质量的评价指标描述不全面,数据质量评价体系不系统等。针对这些问题,提出了以七项指标为基础的全面的数据质量定义,并定义了基于七项指标的十五类数据质量约束规则,给出了它们之间的关系。定义了五元组来形式化描述数据质量评价指标算法,并以完整性评价指标为例详细描述了该算法及其实现过程。为使这些指标与约束规则精准描述及存储,最后基于元数据构建了系列支撑元模型。上述研究成果已在大型企业数据中心数据质量检测与评价中得到了初步应用,并且效果良好。
From the finding of the research on the definition and assessment of data quality abroad and at home,research on these issues still exist many defects,such as the nonuniform definition of data quality ,the incomprehensive description of data quality assessment,the unsystematic system of data quality assessment, etc. Aiming at these issues, give a comprehensive definition of data quality from the seven kinds of assessment indicators. Then define fifteen kinds of constraint rules of data quality based on the seven kinds of assessment indicators. And describe the relationship between them. Quintuple form is defined to formally describe the algorithm of the data quality assess ment indicator. And the integrity assessment indicator is taken as an example to specifically describe the algorithm and its implementation. As for the accurate description and store of these indicators and constraint rules, a series of supporting rectamodels are constructed based on metadata. Research above has preliminarily been applied in the data quality testing and assessment of data center in large enterprises with good results.
出处
《计算机技术与发展》
2013年第3期81-84,89,共5页
Computer Technology and Development
基金
黑龙江省教育基金项目(11541008)
关键词
数据质量
数据质量评价指标
数据质量约束规则
数据质量评价指标算法
元数据
数据质量评价模型
data quality
data quality assessment indicator
data quality constraint rule
algorithm of data quality assessment indicator
meta-data
data quality assessment model
