The proliferation of semantic data on the Web requires RDF database systems to constantly improve their scalability and efficiency. At the same time, users are increasingly interested in investigating large collections of online data by performing complex analytic queries (e.g.,“how did university student performance evolve over the last 5 years?”). This paper introduces a novel benchmark for evaluating and comparing the efficiency of Semantic Web data management systems on analytic queries. Our benchmark models a real-world setting derived from the Bologna process and offers a broad set of queries reflecting a large panel of concrete, data-intensive user needs.