Computational Intelligence Techniques for Big Data Analytics: A Contemplative Perspective

Abstract

AbstractBig data analytics has become an area of great research potential with the emergence of enabling technologies of Web 3.0 and Web 4.0. The proliferation of mobile devices, sensor devices, cloud computing and cyber-physical systems has generated such huge amount of data that if analysed properly are an asset to any organisation or institution. Traditional methods for data analysis are no longer sufficient to handle this data. So, newer and more efficient tools and technologies need to be developed to tap this potential. Computational intelligence techniques like artificial neural networks, evolutionary intelligence, genetic algorithms, federated machine learning, etc., are some of the methods used for big data analytics. In this regard, this paper aims to address the details of different computational intelligence techniques used for big data analytics and provide an in-depth detail of each technique. This study will provide insights and knowledge to the research community to have a one-stop solution to identify the pros and cons of various computational techniques. Further researchers will be able to identify which technique will suit their particular analytics problem at hand.KeywordsEvolutionary computingStrategic decision-makingData analyticsArtificial neural networksFederated learning