A Review on Costing Issues in Big Data Analytics

Abstract

In 2004, Wall Mart guaranteed to have the biggest information stockroom with 500 terabytes stockpiling (identical to 50 printed accumulations of the US Library of Congress). In 2009, eBay stockpiling added up to eight petabytes (think about 104 years of HD-TV feature). After two years, the Yahoo distribution center totalled 170 petabytes1 (8.5 seasons of all hard circle drives made in 1995)2. Since the ascent of digitisation, undertakings from different verticals have amassed thriving measures of advanced information, catching trillions of bytes of data about their clients, suppliers and operations. Information volume is likewise developing exponentially because of the blast of machine-created (information records, web-log documents, sensor information) and from developing human engagement inside of the interpersonal organizations. So for handling this huge amount of data is really a big challenge, so it turns towards the concept of big data. This paper try to cover major aspects of big data is discussed in II Important Aspect's in Big Data along with its costing issues. The issues in transformation of traditional database into big data is discussed in III important points in transition from traditional data base to big data. © 2015 IEEE.