A Framework for Processing and Analysing Real-Time data in e-Commerce Applications

Abstract

In general, predicting Stock Market is quite a demanding task, and targeting very high accuracy is not exactly going to work. Nonetheless, few techniques in machine learning provide relevant predictions. The performances of the generated models were not always completely accurate but lot of errors were present in them. Many papers have been analysed and the methodology used by various authors, their requirements, and the challenges faced by them while building their respective models have been understood. The purpose of this study is to examine some of the numerous analytic techniques and tools that may be used with big data, as well as the potential created by their use in various decision-making areas. Around 242 papers have been collected and up to 38 papers have been filtered among them. Each of them has been filtered based on various factors. Some papers have been excluded based on title, few were excluded based on abstract and titles. The collected papers have been divided into various categories like big data analysis, studies on stock market analysis, research on real time data analysis, papers on Kafka and cloud computing.