Data Quality by Yang W. Lee, Leo L. Pipino, James D. Funk, Richard Y. Wang

By Yang W. Lee, Leo L. Pipino, James D. Funk, Richard Y. Wang

Info caliber offers an exposé of analysis and perform within the info caliber box for technically orientated readers. it truly is in response to the study carried out on the MIT overall facts caliber administration (TDQM) application and paintings from different top learn associations. This booklet is meant essentially for researchers, practitioners, educators and graduate scholars within the fields of machine technology, details know-how, and different interdisciplinary components. It kinds a theoretical origin that's either rigorous and suitable for facing complicated concerns concerning information caliber. Written with the objective to supply an summary of the cumulated study effects from the MIT TDQM learn point of view because it pertains to database study, this ebook is a wonderful advent to Ph.D. who desire to extra pursue their learn within the facts caliber region. it's also an exceptional theoretical advent to IT execs who desire to achieve perception into theoretical ends up in the technically-oriented facts caliber zone, and follow a number of the key suggestions to their perform.

Show description

Read or Download Data Quality PDF

Similar data modeling & design books

Polynomial Algorithms in Computer Algebra

For a number of years now i've been instructing classes in laptop algebra on the Universitat Linz, the collage of Delaware, and the Universidad de Alcala de Henares. within the summers of 1990 and 1992 i've got prepared and taught summer season colleges in computing device algebra on the Universitat Linz. progressively a collection after all notes has emerged from those actions.

Data Dissemination and Query in Mobile Social Networks

With the expanding popularization of private handheld cellular units, extra humans use them to set up community connectivity and to question and percentage information between themselves within the absence of community infrastructure, growing cellular social networks (MSNet). due to the fact that clients are just intermittently hooked up to MSNets, consumer mobility may be exploited to bridge community walls and ahead information.

Big Practical Guide to Computer Simulations

"This certain ebook is a musthave for any pupil trying first steps in computing device simulations. Any new scholar becoming a member of my computational physics workforce is anticipated to first paintings via Hartmann's advisor sooner than beginning a study venture. " Helmut Katzgraber affiliate Professor Texas A&M collage "This ebook is filled with priceless details for everybody doing desktop simulations.

Additional info for Data Quality

Example text

14 Introduction Chapter 1 Improve IP Once the analysis phase is complete, the IP improvement phase can start. The IP team needs to identify key areas for improvement such as: (1) aligning information flow and workflow with infrastructure, and (2) realigning the key characteristics of the IP with business needs. As mentioned earlier, the Information Manufacturing Analysis Matrix [5] is designed for the above purposes. Also, Ballou and Tayi [3] have developed a framework for allocating resources for data quality improvement.

On the other hand, once a conceptual schema that incorporates application, application quality, and data quality requirements is obtained and the corresponding database system developed, then view mechanisms can be applied to restrict views that correspond to each of these types ofrequirements. This leads to the following principle: The Data Quality (DQ) Separation Principle: Data quality requirements are modeled separately from application requirements and application quality requirements. MODELING DATA QUALITY REQUIREMENTS Underlying the Data Quality Separation Principle is the need to measure the quality of attribute values.

E. Madnick, Connectivity among information systems. Vol. 1. Cornposite Information Systems (CIS) Project, MIT Sloan School of Management, Cambridge, MA, 1988. [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 [30] 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.

Download PDF sample

Rated 4.38 of 5 – based on 29 votes