Nowadays, companies are concentrating on more data to take informed decisions. Huge amount of investment is made in storing and processing large amounts of data to make better decisions. The term ‘Big Data’ is derived from the fact that the datasets are so large that typical database systems are not able to store and analyze the datasets (Manyika et al., 2011). The processing of big data is done by using MapReduce. However, big data entails a huge commitment of hardware and processing resources, making adoption costs of big data technology prohibitive to small and medium-sized businesses. Cloud computing offers hardware and processing resources for big data implementation. This paper describes benefits and applications of big data in various industry verticals, popular big data tools available in the market and their capabilities. Some of the areas like banking, travel and healthcare where big data finds application have been discussed.

Enormity of the data and its interpretation for drawing business benefits is one of the challenges being faced by the enterprises of the day. This problem is only going to get worse by the day. In this context, to deal with big data, the technologies have acquired importance these days. Big data are datasets that are so large that they become awkward to work with using currently available tools. In the present generation of digital universe, huge amount of data is added to Internet daily. There is a lot of requirement to analyze this data for constructing a knowledge-based society. For extracting better knowledge, there is always a need for much bigger amount of data. Companies such as Google, Facebook and Linkedin are dealing with bulk of data. This huge amount of data is called big data. Roger Magoulas from O’Reilly media introduced the term ‘Big Data’ in 2005. According to Gartner, big data is defined as follows:

Big data is high-volume, high-velocity and high-variety information asset that demands cost-effective and innovative forms of information processing for enhanced insight and decision making.

Big data implementation requires a large infrastructure support for which companies need to concentrate on establishing computing model that require large centralized data center to store and process huge amount of information. Revolution in memory technology and evolution of multi-core processors have made big data implementation possible in large enterprises. In-memory analytics has brought significant changes in the implementation of querying data by loading data from multiple sources directly into system memory instead of physical disk. This paper presents an overview of big data analysis and its role in today’s IT industry.

Information Technology Journal, Big data, MapReduce, Apache Hadoop.