A C Omprehensive S Tudy O N P Otential R Esearch

Companies, organizations and policy makers shake out with flood flowing volume of transactional data, accumulating trillions of bytes of information about their customers, suppliers and operations. The advanced networked sensors are being implanted in devices such as mobile phones, smart energy meters, automobiles and industrial machines that sense, generate and transfer data to multiple storage devices. In fact, as they go about their business and interact with individuals, they are producing an incredible amount of fatigue digital data. Social media sites, smart phones, and other customer devices have allowed billions of individuals around the world to contribute to the amount of data available. In addition, the extremely increasing size of multimedia data has also take part a key role in the rapid growth of data. The technology of high-definition video creates more than 2,000 times as many bytes as necessary to store as normal text data. Moreover, in a digitized world, consumers are leaving enormous amount of data about their day-today communicating, browsing, buying, sharing, searching and so on. As a result, it evolved as a big data and in turn has motivated the advances in big data analytics paradigms, endorsed as a basic motivation factor for the present researchers. The authors in the present paper conduct a comprehensive study to explore the impact of big data analytics in key domains namely, Health Care (HC), Retail Industry (RI), Public Governance (PG), Pubic Security & Safety (PSS) and Personal Location Tracking (PLT). Initially, the study looks at the insights of data sources along with their characteristics in each domain. Later, it presents the highly productive and competitive big data applications with innovative big data technologies. Subsequently, the study showcases the impact of big data on each domain to capture value addition in its services. Finally, the study put forwards many more research opportunities as all these domains differ in their complexity and development in the usage of big data analytics.