A hybrid approach to assessing data quality
A hybrid approach to assessing data quality
复制标题
评估数据质量的混合方法
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
A. Parlikad
中科院分区：
文献类型：
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作者：
Philip Woodall;A. Parlikad
已提出了各种技术，使各组织能够启动程序，以评估并最终提高其数据的质量。这些评估技术（AT）的效用已被证明在不同的组织环境。然而，虽然一些AT面向特定的应用领域，并且通常不适合不同的应用，但其他AT更通用，因此并不总是满足特定的要求。为了解决这个问题，我们提出了混合的方法来评估数据质量，它可以生成可用的AT的特定要求，使用现有的AT的活动。对现有数据质量（DQ）AT进行了文献综述和自下而上的分析，以确定每个AT提出的不同活动。根据资产管理组织的示例要求，使用混合方法将活动组合在一起，以生成AT，该AT可以用于评估现有的DQ问题。混合的方法表明，它是可能的开发新的方式来评估DQ，利用现有的AT提出的最佳实践相结合的活动动态。
: Various techniques have been proposed to enable organizations to initiate procedures to assess and ultimately to improve the quality of their data. The utility of these assessment techniques (ATs) has been demonstrated in different organizational contexts. However, while some of the ATs are geared towards specific application areas and are often not suitable in different applications, others are more general and therefore do not always meet specific requirements. To address this problem we propose the Hybrid Approach to assessing data quality, which can generate usable ATs for specific requirements using the activities of existing ATs. A literature review and bottom-up analysis of the existing data quality (DQ) ATs was used to identify the different activities proposed by each AT. Based on example requirements from an asset management organization, the activities were combined using the Hybrid Approach in order to generate an AT which can be followed to assess an existing DQ problem. The Hybrid Approach demonstrates that it is possible to develop new ways of assessing DQ which leverage the best practices proposed by existing ATs by combining the activities dynamically.