Systematic investigation on LargeScale simulations in big data systems

The generation of data was confined, and it was rare that online systems were counted on for storing the data in earlier systems. All was on paper. With the rise of technology, a digital revolution gas taken place. All the industries, varying from hospitals to small business to social media websites, are working on the concept of sending data to database, further on to servers, and getting back the response from the server that data has been processed either successfully or unsuccessfully through the reflected response message. On the other hand, the worst part, again ironically, is that to handle the enormous data, a high-tech server or the high tech workplace has to be generated. For the handling of this data, the concept of Big Data has come in limelight. The Big Data has rapidly developed and achieved success in almost all the working fields. It helps to synchronize the data sequentially as the action or the processing has been done. The implementation of Big Data has to be done through simulations, the concept of Artificial Intelligence. So, it's evident that handling data storage has migrated from manual processing to artificial intelligence. This paper aims to study the simulation of Big Data at a large scale and how it can help to store the enormous data virtually effectively and efficiently.