This chapter starts a series of three (with Chapters 5 and 6) that focus on data linkage applied to big data within the context of social policy. Data linkage brings together information from different sources about the same person to create a new, richer dataset that can be used for research or policy (United Nations Statistical Office, 1991). The complex process of data linkage (OAIC, 2014) involves the technical challenges of data matching and subsequent data analysis (Tahamont et al., 2020). Within the linkage process, data matching refers to the technical effort that ensures that individual identities are faithfully matched when combining datasets (Harron et al., 2017). Data analytics enables big data to be exploited, reshaping raw data into information crucial to understanding and decision-making (Mikalef et al., 2020). Given these powerful abilities, data linkage is now widely used by government agencies throughout Australia, including those with a key role in social policy research and development. Specialist institutions conduct data linkage and manage the complex process. For instance, the Australian Institute for Health and Welfare and the Australian Institute for Family Studies note as part of their mandate: “Our linking of data sets provides valuable new information for research and policy-making, in a secure, privacy-preserving manner” (http://www.aifs.gov.au/our-workresources/data-linkage). In these three chapters, the analysis and discussion draw out some of the ways in which data linkage can support richer use of information, with examples from recent policy initiatives, but importantly, they also identify the risks that are involved.