Harnessing supremacy of big data in retail sector via hadoop

Abstract

In today’s world of IT revolution, the data generated in most organizations is voluminous, heterogeneous and at high velocity which is popularly known as Big data. Data in the retail industry is increasing exponentially. In today’s hyper-competitive sales environment, buyers compare prices on the web and share their experiences on the Internet-good, bad, and neutral. So, retailers are increasingly turning to predictive analytics to fulfill the needs of their customers to get maximum profit. The Large volume of data is generated across their supply chains at point-of-sale and at same time data explosion can be experienced from social media and weblogs. Analysis of this huge heterogeneous data can provide the greater opportunities for retailers to win in today’s competitive market. Because of Volume, Velocity, and Variability of this data, it is difficult to handle it by using traditional database management tools. Special tools are used to handle Big Data. Apache Hadoop is one such framework which is capable of handling huge databases via its several components. This research paper focus on overcoming the hurdles of big data i.e. huge heterogeneous data in the retail sector. In this paper, how to handle structured and unstructured big data is discussed. The main objective of this research paper is to use big data analytic for analyzing retail data to better understand customers in a systematic manner, so that retailer can take better decisions.