Utility-driven configuration of data quality in data repositories

The economic benefits of data quality have rarely been researched and quantified. Does the business benefit gained justify the high cost of data quality improvement? Understanding these costs and benefits can direct and improve the implementation and maintenance of data repositories. Here we evaluate the effects of targeted quality levels in data repositories - targeting higher completeness and/or accuracy increases the utility of the data, but involves higher costs. Modelling utility cost effects helps assess quality configuration tradeoffs for optimising economic performance of data repositories. Using the model, we examine different configurations and demonstrate the effect of economics-driven evaluation on data management decisions.