Abstract: Big data is the term for any collection of large and complex data which becomes difficult to process using traditional data processing applications. The challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and privacy violations. Recent times have witnessed the generation and storage of large amount of vital data by various industries which is rapidly increasing on the internet and thus the data scientists are facing a lot of challenges for maintaining a huge amount of data as the fast growing industries require the significant information for enhancing the business and for predictive analysis of the information. The question of the hour is, how to develop a high performance platform that efficiently analyzes big data and how to design an adroit algorithm for mining the useful things from big data. Facilitation of information flows and mechanisms of learning and coordination by heterogeneous individuals is the primary role of big data in cities [4]. However, processes of self-organization in cities, as well as of service improvement and expansion must rely on general principles that enforce necessary conditions for cities to operate and evolve. Such ideas are the core a developing scientific theory of cities, which is itself enabled by the growing availability of quantitative data on thousands of cities worldwide, across different geographies and levels of development. Performing computation and database operations for massive amounts of data, remotely from the data owner’s enterprise is the implication of Big Data. Since a key value proposition of big data is access to data from multiple and diverse domains, a very important role shall be played by Security and Privacy for the technology and implementations.

Keywords: Big data characteristics (Four Vs), big data analytics, big data application, Connectivity between Big data with IoT and cloud, big data limitations, Security and privacy preservations in big data.