By Richard Y. Wang, Mostapha Ziad, Yang W. Lee (auth.)
Data Quality offers an exposé of study and perform within the facts caliber box for technically orientated readers. it truly is in response to the examine carried out on the MIT overall info caliber administration (TDQM) software and paintings from different major study associations. This ebook is meant basically for researchers, practitioners, educators and graduate scholars within the fields of desktop technology, info know-how, and different interdisciplinary parts. It kinds a theoretical beginning that's either rigorous and appropriate for facing complicated matters concerning info caliber. Written with the target to supply an summary of the cumulated learn effects from the MIT TDQM examine standpoint because it pertains to database learn, this booklet is a superb advent to Ph.D. who desire to extra pursue their study within the information caliber quarter. it's also a great theoretical creation to IT execs who desire to achieve perception into theoretical leads to the technically-oriented facts caliber zone, and observe many of the key ideas to their practice.
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29] Wang, Y. R. and S. E. Madnick, "Facilitating connectivity in composite information systems," ACM Data Base, 20(3), 1989, pp. 38-46. Conclusion 35  Wang, Y. R. and S. E. Madnick. "The inter-database instance identification problem in integrating autonomous systems," in Proceedings of the Fifth International Conference on Data Engineering. Los Angeles, CA: pp. 46-55, 1989.  Wang, Y. R. and S. E. Madnick. "A Polygen Model for Heterogeneous Database Systems: The Source Tagging Perspective,".
It applies a knowledge-based approach in data quality judgment to provide flexibility advantages in dealing with the subjective, Overview 51 decision-analytic nature of data quality judgment. The data quality reasoner provides a framework for representing and reasoning with local relationships among quality parameters to produce an overall data quality level to assist data consumers in judging data quality, particularly when data involved in decision-making come from different and unfamiliar sources.
A quality schema is defined as a set of quality scheme sets that describes the structure of a quality database. 2 illustrates the relationship among quality schemes, quality indicator schemes, quality scheme sets, and the quality schema. 2: 27 Quality schemes, quality indicator schemes, quality scheme sets, and the quality schema Ifqr1 is a quality relation and a an attribute in qr1 that has quality indicators associated with it, then the quality key for a must be non-null. Ifqr2 is a quality indicator relation containing a quality indicator tuple for a, then all the attributes ofqr2 are called level 1 quality indicators for a.