Market basket analysis is one of the data mining methods focusing on discovering purchasing patterns by extracting associations or co-occurrences from a store’s transactional data. Market basket analysis is an important component of analytical system in retail organizations to determine the placement of goods, designing sales promotions for different segments of customers to improve customer satisfaction and hence the profit of the supermarket. Data mining finds interesting patterns from databases such as association rules, correlations, sequences, classifiers, clusters and many more of which the mining of association rules is one of the most popular problems. 1. Association rule Association rule mining finds interesting association or correlation relationships among a large set of data items. Association rules are derived from the frequent itemsets using support and confidence as threshold levels. The sets of items which have minimum support are known as Frequent Itemset.