Impact of the Union and Difference Operations on the Quality of Information Products
Amir Parssian,
Sumit Sarkar,
Varghese S. Jacob
Department of Information Systems, Instituto de Empresa Business School, Madrid 28006, Spain
School of Management, University of Texas at Dallas, Richardson, Texas 75080
School of Management, University of Texas at Dallas, Richardson, Texas 75080
amir.parssian{at}ie.edu
sumit{at}utd.edu
vjacob{at}utd.edu
Information derived from relational databases is routinely used for decision making. However, little thought is usually given to the quality of the source data, its impact on the quality of the derived information, and how this in turn affects decisions. To assess quality, one needs a framework that defines relevant metrics that constitute the quality profile of a relation, and provides mechanisms for their evaluation. We build on a quality framework proposed in prior work, and develop quality profiles for the result of the primitive relational operations Difference and Union. These operations have nuances that make both the classification of the resulting records as well as the estimation of the different classes quite difficult to address, and very different from that for other operations. We first determine how tuples appearing in the results of these operations should be classified as accurate, inaccurate or mismember, and when tuples that should appear do not (called incomplete) in the result. Although estimating the cardinalities of these subsets directly is difficult, we resolve this by decomposing the problem into a sequence of drawing processes, each of which follows a hyper-geometric distribution. Finally, we discuss how decisions would be influenced based on the resulting quality profiles.
Key Words: information quality framework; relational data model; probability calculus; hyper-geometric distributions; database marketing
History: This paper was received on February 28, 2006.
Copyright © 2008 by INFORMS.
