articleTop 1% cited
Data quality assessment
Communications of the ACM · 2002 · Vol. 45(4) · pp. 211–218
Leo L. Pipino✉(University of Massachusetts Lowell)Yang W. Lee(Northeastern University)Richard Y. Wang(Boston University)
Abstract
How good is a company's data quality? Answering this question requires usable data quality metrics. Currently, most data quality measures are developed on an ad hoc basis to solve specific problems [6, 8], and fundamental principles necessary for developing usable metrics in practice are lacking. In this article, we describe principles that can help organizations develop usable data quality metrics.
Data Quality and ManagementBig Data and Business IntelligenceData-Driven Disease SurveillanceUSableComputer scienceQuality (philosophy)Data qualityData scienceData miningWorld Wide WebEngineeringOperations managementMetric (unit)
Citations
1,630
FWCI
28.78
field-weighted impact
References
10
Percentile
100%
vs. same field & year
Citations per year
Cited by
Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications
International Journal of Production Economics · 2014 · 838 citations
Methodologies for data quality assessment and improvement
ACM Computing Surveys · 2009 · 1,227 citations
References
Anchoring data quality dimensions in ontological foundations
Communications of the ACM · 1996 · 1,452 citations
Citation Network
How this paper connects to the literature. Drag to explore, click any node to open that paper.