Organizations that aim to achieve their strategic objectives and rely on data to support operational and decision-making processes must possess a clear understanding of the extent to which their data fulfills established quality criteria. These criteria are typically enunciated through specific data quality dimensions. In academic and professional contexts, data quality assessment frameworks often necessitate the implementation of mechanisms for the systematic monitoring and control of data quality levels. The introduction of a methodology that integrates a qualitative assessment of data quality dimensions–supplemented by data profiling techniques to quantify selected dimensions–can significantly enhance the effectiveness and reliability of data utilization. The principal contribution of this proposal is the development of a comprehensive methodology for evaluating data quality through the combined use of survey-based diagnostic tools and data profiling techniques. Furthermore, the paper presents the outcomes of a case study, which serves to validate the proposed methodology within a real organizational setting.
Guerra-García et al. (Mon,) studied this question.