Understanding the differences across data quality classifications: a literature review and guidelines for future research

Purpose Numerous data quality (DQ) definitions in the form of sets of DQ dimensions are found in the literature. The great differences across such DQ classifications (DQCs) imply a lack of clarity about what DQ is. For an improved foundation for future research, this paper aims to clarify the ways in which DQCs differ and provide guidelines for dealing with this variance. Design/methodology/approach A literature review identifies DQCs in...