Today, a myriad of data is generated via connected devices and digital applications. With recent ad- vances in artificial intelligence (AI), companies are seeking new opportunities to monetize data. This goes along with improving their capabilities to manage big data and analytics (BDA). A critical factor that is often cited concerning the ‘soft’ aspects of BDA is data ownership, i.e. clarifying the funda- mental rights and responsibilities for data. Scholars have investigated data ownership for operational systems and data warehouses, where the purpose of data processing is known. In the BDA context, defining accountabilities for data ownership is more challenging, because data is stored in data lakes and used for new, previously unknown purposes. Based on insights from three case studies with exten- sive experience in BDA, we identify ownership principles and three data ownership types: data, data platform, and data product. By redefining the concept of data ownership, our research answers fun- damental questions about how data management changes with BDA, extending existing concepts on data ownership and contributing to the data governance literature.