Association rule discovery is one of the most important techniques in the field of data mining. It aims at finding interesting patterns among the databases. However it becomes much tedious to mine the association rules as the data are growing more and more like mountain. Hence it is important in developing techniques in such a way that interesting rules are mined effectively from huge databases. This paper provides an overview of techniques that are used to improvise the efficiency of Association Rule Mining (ARM) from huge databases.