Data mining can be defined as the process of analysing mostly large data sets to explore and discover previously unknown patterns, trends and relationships to generate information for better decision making. Although data mining has primarily been developed and applied in commercial sectors, it can also be usefully applied in non-commercial sectors, including in education. With the substantial amount of data collected in education (e.g., student characteristics and performance results), such raw data will not be useful for decision making unless and until they are transformed into information. This is where data mining can play a useful role by extracting relationships from the vast amount of data. This paper discusses the usefulness of data mining in education and illustrates it using two case studies.