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Data are increasingly important in central facets of modern life: academics, professions, and society at large. Educating aspiring minds to meet highest standards in these facets is the mandate of institutions of higher education. This, naturally, includes the preparation for excelling in today’s data-driven world. In recent years, an intensive academic discussion has resulted in the distinction between two different modes of data related education: data science and data literacy education. As a large number of study programs and offers is emerging around the world, data literacy in higher education is a particular focus of this paper. These programs, despite sharing the same name, differ substantially in their educational content, i.e., a high plurality can be observed. This paper explores this plurality, comments on the role it might play and suggests ways it can be dealt with by maintaining a high degree of adaptiveness and plurality while simultaneously establishing a consistent educational “essence”. It identifies a skill set, data self-empowerment, as a potential part of this essence. Data science and literacy education are still experiencing changeability in their emergence as fields of study, while additionally being stirred up by rapid developments, bringing about a need for flexibility and dialectic.