Good explanatory constructs for Data, Information and Knowledge, and related theory of their interaction, are central to efforts to generate valuable insights from the significant, evolving growth in Data. The central role of Knowledge within such a theory has been highlighted recently, as well as the importance of Learning and Research frames for Data Analytics. Building on these ideas, this paper briefly reviews several related literatures, for relevant ideas to enrich IS theory building. A consensus is found as to the complex, socially constructed nature of Knowledge or Knowing, and the importance of human sensemaking for theorizing how new insight or Knowledge is generated. The paper argues for an intuitive conceptual and practical distinction between Data (which exists as an independent, reified resource), and Information and Knowledge (both of which are embodied or embrained). It also highlights specific areas for further inter-disciplinary engagement and research within the context of Analytics.