Data products are seen as important levers in repurposing the large volumes of data that are captured in organizations and in satisfying the increasing demand for analytics. Despite the increasing popularity of the data product concept, it remains unclear how data can be productized. This article proposes work system theory to study the implications data products have for how organizations manage their data. Adopting a multimethod approach involving case studies and focus groups, we identify three types of data products and analyze how organizations coordinate their resources to build work systems around each data product type. Our findings contribute to the ongoing discourse on scaling data and analytics capabilities to repurpose and consume data effectively.