Methods for the Identification of Data Outliers in Interactive SQL

Methods for the Identification of Data Outliers in Interactive SQL

Ronald Dattero (Florida Atlantic University, USA), Edna M. White (Florida Atlantic University, USA) and Marius A. Janson (University of Missouri-St. Louis, USA)
Copyright: © 1991 |Pages: 12
DOI: 10.4018/jdm.1991010102
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Abstract

The purpose of this paper is twofold. First, the paper discusses the importance of identifying data outliers (that is, extremely unusual values) for three major purposes in the management of database systems: (1) data validation, (2) statistical analysis, and (3) extreme point recognition. Outliers are defined following the original approach developed by Tukey for use in Exploratory Data Analysis. Second, the paper develops two outlier identification procedures that can be directly inserted into relational database systems through the nonprocedural relational database language SQL (Structured Query Language). The first procedure, the Hinge Procedure, follows exactly Tukey’s definition of outliers, but requires the creation of an additional base table. The second procedure, the Quartile Procedure, provides only a close approximation to Tukey’s definition, but can be implemented solely through views. The development of these procedures was non-trivial due to the rather limited number of available mathematical functions in SQL. The advantages and disadvantages of the two procedures are discussed in the paper.

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