With slogans such as ‘Tell the stories hidden in your data’ (www.narrativescience.com) and ‘From data to clear, insightful content – Wordsmith automatically generates narratives on a massive scale that sound like a person crafted each one’ (www.automatedinsights.com), a series of companies currently market themselves on the ability to turn data into stories through Natural Language Generation (NLG) techniques. The data interpretation and knowledge production process is here automated, while at the same time hailing narrativity as a fundamental human ability of meaning-making. Reading both the marketing rhetoric and the functionality of the automated narrative services through narrative theory allows for a contextualization of the rhetoric flourishing in Big Data discourse. Building upon case material obtained from companies such as Arria NLG, Automated Insights, Narrativa, Narrative Science, and Yseop, this article argues that what might be seen as a ‘re-turn’ of narrative as a form of knowledge production that can make sense of large data sets inscribes itself in – but also rearticulates – an ongoing debate about what narrative entails. Methodological considerations are thus raised on the one hand about the insights to be gained for critical data studies by turning to literary theory, and on the other hand about how automated technologies may inform our understanding of narrative as a faculty of human meaning-making.