Analysis of big data for data-intensive applications

In the recent decade big data has attracted attention from decision and policy makers in enterprises and governments, market analysts, and data scientists. The growth of information in the current decade has exceeded the Moore's law, and the vast amount of data is increasing the pain towards managing and analyzing. However, this high amount of data has a great potential and extremely useful information is hidden in it. Data-intensive scientific discovery helps to identify big data problems. The big data problems are found in various areas and sectors such as economic activities to provide effective public administration, national security, and scientific research. Several progressions in various fields were made possible because of big data and there is no doubt that the future challenges in business enhancements will converge to explore big data. Few difficulties that arise in big data are data visualisation, data storage, data analysis, and data capture. The aim of our paper is to give a clear idea about big data and its data-intensive applications. We have also covered several schemes to handle quantum computing, bio-inspired computing, cloud computing, and granular computing.