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Methods for the Quality of Data in Databases

机译:数据库中数据质量的方法

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摘要

This paper contains possibilities to improve the quality of the (meta) data of the Central Relations Database (CRD) of a Dutch insurance company. This research provides methods and tools to measure and evaluate the quality of data (measure methods). Main causes of problems with the Quality of Data (QoD) are: the unclear, inconsistent and missing delivery of data and the absence of formal work procedures. This causes problems like false data in the database, data loaded at the wrong place, too many administrative activities, unclear conceptual models, difficulties in interpreting the meaning of data elements, etc. This means that procedures and methods have to be developed and applied to reach the desired QoD for both the user-organization and the data process-organization (corrective methods). Additional solutions are: introduction of formal documentation, development of uniform systems, replacement of the Data Dictionary System, enhancement of systems developers' responsibilities and creating a new function to store knowledge of employees. A general approach will be proposed.
机译:本文包含改善荷兰保险公司中央关系数据库(CRD)的(元)数据质量的可能性。这项研究提供了测量和评估数据质量的方法和工具(测量方法)。数据质量(QoD)问题的主要原因是:数据传递不清楚,不一致和丢失以及缺少正式的工作程序。这会导致诸如数据库中的错误数据,在错误的位置加载数据,太多的管理活动,不清楚的概念模型,难以解释数据元素的含义等问题。这意味着必须开发和应用过程和方法。达到用户组织和数据过程组织所需的QoD(纠正方法)。其他解决方案包括:引入正式文档,开发统一系统,替换数据字典系统,增强系统开发人员的职责以及创建新功能来存储员工的知识。将提出一种通用方法。

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