By Richard Y. Wang, Mostapha Ziad, Yang W. Lee (auth.)
Data Quality offers an exposé of study and perform within the info caliber box for technically orientated readers. it really is in response to the study performed on the MIT overall information caliber administration (TDQM) application and paintings from different top learn associations. This ebook is meant essentially for researchers, practitioners, educators and graduate scholars within the fields of computing device technological know-how, info expertise, and different interdisciplinary parts. It types a theoretical origin that's either rigorous and proper for facing complex concerns concerning info caliber. Written with the target to supply an summary of the cumulated examine effects from the MIT TDQM study point of view because it pertains to database learn, this publication 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 info caliber quarter, and observe a number of the key innovations to their practice.
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The issue is, then, how to use these local dominance relationships between quality parameters, and what can be known about data quality from them. Observe that each local relationship between quality parameters specifies the local relative significance of quality parameters.
However, it does not include the data integrity component. The Attribute-based Model, on the other hand, allows for the structure, storage, and processing of quality relations and quality indicator relations through a quality indicator algebra. In addition, it includes a description of its data structure, a set of data integrity constraints for the model, and a quality indicator algebra. , I. Chengalur-Smith and R. Y. Wang , A Sampling Procedure for Data Quality Auditing in the Relational Environment (No.
E. Madnick. "A Source Tagging Theory for Heterogeneous Database Systems," in Proceedings of International Conference on Information Systems. Copenhagen, Denmark: pp. 243-256, 1990. [33] Yuan, Y. , The design and implementation of system P: A polygen database management system (No. CIS-90-07). MIT Sloan School of Management, Cambridge, MA 02139, 1990 C H A P T E R 3 Extending the ER Model to Represent Data Quality Requirements In the previous chapter, we described how data quality can be incorporated into the relational model.
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