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This qualitative study aims to fill gaps in a widely studied and relevant organizational feature: the alignment between information technologies and business strategies.

This research is a qualitative study. The authors used focus groups, content analysis and semantic networks as research approaches to identify the main factors that prevent or foster such alignment.

Results reveal a leading role of innovation, organizational culture, access to information and financial factors that could promote or inhibit alignment and competitiveness.

This research was conducted only in small and medium organizations in Mexico, which represents about 52% of the Mexican Gross Domestic Product (for Mexico as one of the leading trade partners of the USA).

Studies show that data quality (DQ) issues are extremely costly for companies. To address such issues, as a starting point, there is a need to understand what DQ is. In his context, the 1996 paper “Anchoring data quality dimensions ontological foundations” by Wand and Wang has been highly influential on the understanding of DQ. However, the present study demonstrates that some of the assumptions made in their paper can be challenged. On this basis, this study seeks to develop clearer definitions.

The assumptions behind Wand and Wang’s DQ classification are discussed, on which basis three counter-propositions are formulated. These are investigated through a representation theoretical approach involving analyses of deficient mappings between real-world and information system states. On this basis, an intrinsic DQ classification is derived. A case study is conducted to investigate the value of the developed DQ classification.

The representation theoretical analysis and the case study support the three propositions. These give rise to the development of a DQ classification that includes three primary intrinsic DQ dimensions (accuracy, completeness and conciseness), which are associated with six primary value-level DQ deficiencies (inaccuracy, incorrectness, meaninglessness, incompleteness, absence and redundancy). The case study supports the value of extending Wand and Wang’s DQ classification with the three additional data deficiencies.

By improving the conceptual clarity of DQ, this study provides future research with an improved basis for studies and discussions of DQ.

The study advances the understanding of DQ by providing additional clarity.