The DaTUM framework: a multi-sector thematic analysis of data quality dimensions and their impacting factors

• Multi-sector investigation into data quality dimensions and impacting factors. • A new theoretical framework to support organisational digitalisation or diversification. • A three-step process to apply the framework is presented to evaluate data quality and identify areas for improvement. • Thematic analysis of interviews with 31 practitioners from five sectors. • Four segments of data quality dimensions and five impacting factors are identified. The quality of data is central to decision making across all sectors. However, the many single-application studies, proposing hundreds of dimensions, make data quality assurance a daunting prospect. The diversification of industries is compounding this challenge, making a multi-sector classification essential. We propose a new classification for data quality – the DaTUM framework – which can act as a starting point for data quality assurance across diverse sectors. The framework was developed from reflective thematic analysis of 31 in-depth semi-structured interviews with academics and industry professionals from engineering, policy, economics, computer science, and psychology domains who generate, process, or analyse data. Eleven data quality dimensions and five factors that impact data quality were identified. The DaTUM framework, along with the operationalisation process, will simplify digitalisation and diversification efforts within organisations and support targeted data management and quality improvement strategies which are vital to achieving the true value of data.