Big Data is a term used for a large and a variety of data that is structured, unstructured or hybrid. It comes from different sources at a high speed. It is a data that is too big and complicated to store, analyze and interpret. Big data are broadly comprised of 4 Vs: Volume, Velocity, Variety and Veracity; these make it bigger and much diversified domains. The processing, management and analysis of big data has opened-up a number of research domains. This data is different from traditional relational data and so the Relational Database Management Systems (RDBMS) are incapable to handle it. The RDBMS is inadequate to handle the growth in volume of data, heterogeneity of data and need to store and access it speedily. This necessitated a new type of database functionality to support the real time applications and the Big Data Technologies have emerged.

In this book chapter, we have carried out a detailed survey of this diversified domain, such as Predicting future business possibilities and probabilities, Managing big data through NoSQL databases, Search and knowledge discovery, Real-time data stream analysis, Improving latency rate towards accessing and processing big data in main memory, Managing redundancy and location of distributed big data, Integrating required data through virtualization i.e. without physically moving the high volume of data, Integrating data through a physical movement, Data preparation for useful analytics and Managing data quality.