A dataset is a collection of data. Today the huge amount of the data is being captured by information sensing devices such as mobiles, computers, sensors etc. These huge amounts of the data are now called as big data. Frequent Itemset mining is a tool for identifying the frequently occurring items together. There are many frequent Itemset mining algorithms like apriori, Eclat and FP growth. In the proposed work we use FP growth algorithm and compare it with Apriori algorithm and we show that FP growth algorithm is better when compared to the apriori algorithm.