This study investigates Data Literacy (DL) in German higher education institutions. By employing a qualitative content analysis approach supported by the in Germany widely acknowledged “Future Skills: A Framework for Data Literacy”, this study considers primary the content of course descriptions from educational offers provided by those institutions. We analysed 62 out of 101 offers found and investigated the balance between productive (“coding”) and receptive (“decoding”) competencies as well as what their content includes. We further investigated the structural components of the offers. Results suggest that although course contents vary to meet specific needs of disciplines, the term was generally understood and designed to foster productive competencies (“coding”). Critical thinking in this regard seemed to be understood as an integral part of these very productive processes. Receptive competencies (“decoding”) and the ability to critically consider data detached from a singular productive process received little or no (direct) attention. With the spread of DL into a range of disciplines, a trend towards variation and specialisation in DL was observed. This highlights the adaptability of the term and questions its interoperability at the same time. With a few online available exceptions, offers remain “data literacy islands” with limited access.