A Taxonomy of Factors Influencing Data Quality

Abstract

This paper aims at developing a taxonomy of factors influencing data quality. For this to happen, firstly, we conducted a survey of literature that has focused on examining the factors affecting data quality for the purpose of quality management and improvement in conceptual models. Secondly, referring to a well-established taxonomy development method, we distinguished 5 dimensions of the factors affecting data quality from related studies including: human, organisational, managerial, technical, and external dimensions as well as adding 11 characteristics under different dimensions that are not found in prior classifications. The proposed taxonomy was then evaluated by applying two well-known approaches: users’ navigation exercises and criteria-oriented validation. The evaluation results of this study show that the proposed taxonomy can be used to categorise the factors affecting data quality. The taxonomy will benefit (a) researchers to compare differences between related studies and construct conceptual models of factors affecting data quality and (b) help practitioners improve the understanding of direct causes that improve or reduce data quality from the five dimensions and identify what are the core areas that have an impact on achieving high-quality data for enterprises and should receive more efforts to address data quality.