Since big data analytics has become an imperative for business success in the digital economy, universities face the challenge to train data scientists and data engineers on various technological and managerial skills. In addition to traditional lectures, active learning formats ensure a practice-oriented education enabling students to handle novel big data technologies. In this paper, we present a big data management syllabus for master students in the field of big data analytics, which includes various hands-on and action learning elements. The course encompasses seven lectures and nine tutorials and takes place at Chemnitz University of Technology. It covers a broad range of big data applications and facilitates knowledge on various cognitive levels. The paper gives an overview of the course content and assigns learning objectives to lectures and tutorials using Krathwohl’s revised taxonomy. Finally, we present the feedback, which we have received by the students over the years.
Dinter, Barbara; Jaekel, Tobias; Kollwitz, Christoph; and Wache, Hendrik, "Teaching Big Data Management – An Active Learning Approach for Higher Education" (2017). Proceedings of the Pre-ICIS 2017 SIGDSA Symposium. 1.