Adding big value to big businesses: A present state of the art of big data, frameworks and algorithms

Abstract

Data plays a pivotal role in business growth. In fact, data is considered to be an asset to organizations. This is more evident in the enterprises where the data is preserved and mined for discovering knowledge. The data with exponential growth and characterized by volume, velocity, and variety is termed as big data. Mining such voluminous data can give comprehensive business intelligence for making strategic decisions. The emergence of cloud computing technology, parallel processing power of servers, and the distributed programming frameworks like Hadoop with new programming paradigm “MapReduce” pave way for mining massive-scale data. Data mining domain is rich in algorithms that are used to mine data for discovering trends. The era of big data has arrived and mining such data is beyond the capability of conventional data mining techniques. The unprecedented exponential growth of data needs a platform for effective data analysis in real time with fast response. In this paper, we present an overview of big data, mechanisms or algorithms and environment or tools needed to execute them. The rationale behind this paper is that big data mining is the need of the hour in all sectors like finance, biology, healthcare, banking, insurance, and environmental research to name few. Review of various aspects of big data mining can help readers to gain know-how in the context of globalization, business collaborations where mining cross-organization data is essential. This paper also throws light into the relationship among big data, cloud computing technology, Hadoop, and Big data storage systems. In future, we intend to propose and implement algorithms for big data mining.