A Brief Overview of Data Mining and Analytics in Games

Abstract

The twenty-first century has been repeatedly proclaimed to be the century of data. The increasing processing capabilities of computers and the proliferation of Internet-enabled devices have made it easier than ever to gather more and more data about 2every aspect of our daily lives. The massive amount of data produced every day, however, also needs to be transformed into actual information and knowledge to be of real value and to be of actual use for decision-making. This requires adequate techniques and tools that help uncover hidden and valuable information or patterns within the collected data. Otherwise, the large volumes of data are just that—data bare any deeper meaning. This is the goal of data mining (Kantardzic, 2011). While data mining has been and is receiving considerable attention to be able to cope with the ever-increasing data volumes, the term started to appear in the late 1980s, early 1990s (Coenen, 2011; Dong & Pei, 2007). Data mining is not a single technique but rather a conglomerate of methods, techniques, and algorithms, usually applied in an iterative or explorative process.