The study of data quality (DQ) in information systems (IS) research has gained prominence, particularly in the realm of data repurposing. This process, also referred to as secondary data use, involves using already existing data for a purpose other than initially planned, often by new users who may have limited understanding of data’s contextual nuances. Consequently, quality assessment of repurposed data remains a challenging task, especially regarding contextual DQ. Motivated by this, we examine contextual DQ in secondary data use and investigate how it is achieved in practice. Through interviews with data scientists and analysts, this study uncovers work of those who are involved in data repurposing. By looking at the data through practice lens, we propose strategies for overcoming identified challenges, providing valuable insights for practitioners and researchers, and emphasise the importance of data’s contextual understanding and data work for ensuring DQ.