Big Data Applications for Economic Information Analysis and Decision-Making in the Context of Wireless Communication Networks

Abstract

Systems produce bandwidth in a variety of methods, resulting in an estimated 17.5 exabyte of data generated each week. There exist numerous factors that contribute to data’s growing volume. Technological investigations, for example, can produce a massive amount of data, for example, CERN’s Large Hadron Collider (LHC), which produces about 39 terabytes annually (Table 1). Having more than 1 billion members on Facebook and Twitter, social media contributes largely where individuals allocate an equivalent of 2.5 hours per day liking, tweeting, publishing, and exchanging respective views. Without a question, leveraging interactionproduced data could have an impact on the economics field. Unfortunately, making use of data's potential is a challenging task. To manage the data surge, large-scale storage facilities are being built all the time. One such facility is the National Security Agency (NSA) Utah facility, which can store between 0.5 and 1.5 yottabytes of data and has a computer power of more than 100 petaflops [1].
Frameworks which operated on multiple computers began to spring up as a result of the elevated demand to broaden datasets to large datasets that surpassed operating and/or memory functionalities. Around June 1986, Teradata Corporation utilized the foremost concurrent database framework with just 1-terabyte memory volume in the Kmart data center to preserve and make accessible everything about their company information for interactional inquiries and organizational evaluation (Table 2). The University of Wisconsin’s Gamma framework and the University of Tokyo’s GRACE framework are two such illustrations.