Abstract

As the volume and variety of available data continue to proliferate, organizations increasingly turn to analytics in order to enhance business decision-making and ultimately, performance. However, the decisions made as a result of the analytics process are only as good as the data on which they are based. In this article, we examine the data quality problem and propose the use of control charting methods as viable tools for data quality monitoring and improvement. We motivate our discussion using an integrated case study example of a real aircraft maintenance database. We include discussions of the measures of multiple data quality dimensions in this online process. We highlight the lack of appropriate statistical methods for the analysis of this type of problem and suggest opportunities for research in control chart methods within the data quality environment. This article has supplementary material online.

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