By Richard Y. Wang, Mostapha Ziad, Yang W. Lee (auth.)
Data Quality offers an exposé of analysis and perform within the information caliber box for technically orientated readers. it's in keeping with the examine carried out on the MIT overall information caliber administration (TDQM) software and paintings from different best study associations. This booklet is meant essentially for researchers, practitioners, educators and graduate scholars within the fields of laptop technological know-how, details expertise, and different interdisciplinary parts. It varieties a theoretical origin that's either rigorous and suitable for facing complex matters relating to information caliber. Written with the objective to supply an summary of the cumulated examine effects from the MIT TDQM learn viewpoint because it pertains to database examine, this publication is a wonderful advent to Ph.D. who desire to extra pursue their study within the facts caliber sector. it's also a superb theoretical creation to IT execs who desire to achieve perception into theoretical leads to the technically-oriented information caliber sector, and follow many of the key innovations to their practice.
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Extra info for Data Quality
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. TDQM-00-02). Massachusetts Institute of Technology, 2000.  Ballou, D. P. and H. L. Pazer, "Designing Information Systems to Optimize the Accuracy-Timeliness Tradeoff," Information Systems Research, 6(1), 1995, pp. 51-72.  Ballou, D.
The arrows from Steps 1-2 to Step 3 indicate that application and application quality requirements are modeled before data quality requirements. As in conventional database design and software engineering practices, these steps may be iterated. The distinctions among application requirements, application quality requirements, and data quality requirements are important at both the requirements analysis and conceptual design stages. Both application requirements and application quality requirements are identified to represent a real-world system [5,9].
Let a1 and a2 be two application attributes. Let a1 and a2 be QI-Compatible with respect to S. Let w1 and w2 be values of a1 and a2 respectively, then w1 and w2 are defined to be i-level QI-Compatible if the following two conditions are satisfied: (1) a1 and a 2 are QI-Compatible with respect to S, and (2) S consists of all quality indicators present within i levels ofthe quality indicator tree of a1 (thus ofa2). By the same token, i-level QIV-Equal between w1 and w2, denoted by w1 =i w2, can be defined.
Data Quality by Richard Y. Wang, Mostapha Ziad, Yang W. Lee (auth.)
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