Data Quality Tools: Towards a Software Reference Architecture

Organizations crave to succeed in the ongoing digital transformation, and central to this is the quality of data as a major source for business innovation. Data quality tools promise to increase the quality of data by managing and automating the different tasks of data quality management. However, established tools often lack support for the fundamental changes accompanying an ongoing digital transformation, such as data mesh architectures. In this paper, we propose a software reference architecture for data quality tools that guides organizations in creating state-of-the-art solutions. Our reference architecture is based on the knowledge captured from ten data quality tools described in the scientific literature. For evaluation, we conducted two qualitative focus group discussions using the adapted architecture tradeoff analysis method as a basis. Our findings reveal that the proposed reference architecture is well-suited for creating successful data quality tools and can help organizations assess offerings in the market.