The term “learning analytics” often drives people away because it seems to imply numbers, algorithms and other alien-like terms. This session will unveil these secretive codes and unearth valuable and unexpected treasures in data. In particular, this session will explain how these treasures can help us: 1. identify at-risk students; 2. cluster students with different sets of characteristics; 3. understand associations between students’ weaknesses. These techniques are introduced with an open data source from an institution in the UK.  Colleagues with/without a statistical background are invited to join us on this knowledge discovery journey.