Dr. Neeraj Dahiya et al. International Journal of Recent Research Aspects ISSN: 2349-7688, Vol. 8, Issue 3 September 2021, pp. 4-13 © 2021 IJRAA All Rights Reserved page - 4- Data mining techniques for Big data: Purpose, Techniques and Practical Implications Dr. Neeraj Dahiya 1 , Lavi Tyagi 2 , Neeru Sharma 3 1 Department of CSE, SRM University, Delhi-NCR, Sonipat, Haryana. 2 Department of CSE, Panipat Institute of Engineering & Technology, Panipat, Haryana. 3 M. Tech. CSE, Kurukshetra University, Kurukshetra Haryana. Abstract: The unreasonable development of high dimensional huge information has brought about a more prominent test for information researchers to effectively get important information from these information. Customary Data Mining procedures are not fit to handle large information. Prescient investigation has developed in noticeable quality close by the rise of large information. Association Rule Mining (ARM) is a noteworthy assignment for finding successive examples in Data Mining. It has made extraordinary progress in a plenty of uses, for example, market basket, PC systems, suggestion frameworks, and social insurance. In the previous scarcely any years, developmental calculation based ARM has risen as one of the most well-known examination territories for tending to the high calculation season of conventional ARM. Although various papers have been published, there is no complete examination of existing transformative ARM systems. In this paper, we survey rising examination of developmental computation for ARM. We examine the applications on transformative calculations for various sorts of ARM approaches including mathematical guidelines, fluffy principles, high-utility itemsets, class association rules, and uncommon affiliation rules. Keywords: Data Mining, Big Data, Distributed computing, Hadoop I. INTRODUCTION Mining of Data includes successful information assortment and warehousing just as PC handling. Information digging is utilized for analyzing crude information, including deals numbers, costs, and clients, to grow better showcasing techniques, improve the presentation or decline the expenses of maintaining the business. Additionally, Data mining serves to find new examples of conduct among purchasers [1]. Fig. 1 Data mining techniques