A Study on Covid-19 Analytics on Bigdata

Abstract

Big data enables the rapid generation of massive volume of data from a variety of rich data sources. Using the 2019 coronavirus disease as an example, these enormous data sets contain information on people who have had viral illnesses, as well as information on healthcare and epidemiology. (COVID19). Researchers, epidemiologists, and lawmakers can better comprehend the disease as a result of data scientists' knowledge obtained from these epidemiological data, which may inspire them to create policies for identifying, containing, and combating it. This article outlines a data science methodology for analyzing vast quantities of COVID-19 epidemiological data. This study investigates if early SARS exposure affects imprinting based on the imprinting theory. that has a significant impact fear of COVID-19 In addition, this study suggests the use of big data and AI applications will determine whether this effect occurs. The global economic, social, sociological, and health sectors were severely harmed by the COVID-19 epidemic, which also caused a sizable number of fatalities. The necessary knowledge is developed using the proper big data analytics technologies, which are then used to make judgements and take precautionary action.