Volume : 5, Issue : 9, September - 2016

ISO CERTIFIED AND IMPACT ANALYSIS OF DATA QUALITY FRAMEWORK

Srashti Rane, Pravin Metkewar

Abstract :

<p>&nbsp;Data Quality is cross-discipline, precondition for analyzing and domain specific problem due to the importance of fitness use in the data quality metric. However, the changing landscape of data quality challenge tells the need for holistic solution. As a step on idging any gaps in the various research communities, we undertook a comprehensive literature study of data quality is been done. First, this paper summarizes reviews of data quality research. Second, this paper analyzes the data characteristics of the data environment, presents quality challenges faced by data, and expresses a hierarchical data quality framework from the views of various data users. This framework consists of quality dimensions, quality characteristics, and different quality indexes. Finally, on the basis of the framework, the paper constructs a dynamic assessment process for data quality. This process consists of good extensibility and flexibility and can meet the requirements of data quality assessments. The research results enrich the theoretical scope and model of data and lay a solid foundation for the future for establishing an assessment model and studying evaluation algorithms.</p>