This entry provides an overview of empirical work focused on vocabulary as related to data-driven learning (DDL). Situated in the broader context of corpus analysis and corpus-informed language pedagogy, the entry introduces DDL as a research area that is integral to vocabulary studies, showcasing the main premises of corpus-based language learning and teaching and summarising the main findings in terms of their theoretical and practical relevance. Specifically, after the introductory part defines DDL, the subsequent sections offer a discussion of the key issues pursued in DDL research as pertinent to vocabulary, understood as both individual words and multiword units. This discussion is built around selected examples of DDL studies that are of interest to vocabulary research while at the same time demonstrates the value of DDL and corpus-based research more broadly in language pedagogy. In its latter part, the entry calls for revamping the notion of DDL in vocabulary studies, expanding its theoretical and methodological basis and benefiting from developments within the field of computer-assisted language learning (CALL). Instances of research questions and the main findings are also discussed, outlining the scope of CALL studies focused on vocabulary.