Data Mining is the process of extracting useful information from a large set of data. Market Basket Analysis is a technique of data mining which discovers an association between items with another. Market Basket Analysis refers to a process or technique, which identifies a customer's buying behavior or purchasing pattern, i.e. the items which are bought together by a customer in a single shopping cart. Market Basket Analysis is also termed as Association rule learning and another name for this technique is affinity Analysis. The main purpose of Market Basket Analysis is to extract the purchasing pattern of customers so that it increases the business efficiency and assists the retailers in making the decision regarding business in a profitable direction, increasing sales and make marketing strategies to compete with competitors. The main challenge for leading supermarkets is to attract a good number of customers, which can be done with the help of a data mining technique that is association rule mining. The frequent item sets are mined from the market basket to generate and after generation of the frequent items, the strongly associated item sets are generated with the help of support and confidence. This paper presents a recent survey of a supermarket for generating association rules to examine the customers’ buying or purchasing behavior.