Abstract
Big data application has found drastic growth in every field since it estimates an appropriate result, and it can handle any volume of data. Data analytics models predict the target through which rise or fall of each data can be identified. Big data, when combined with data analytics, overcomes all the traditional technology and provides the best solution. COVID-19, a disease that came into the picture as it emerged from Wuhan city, China, made a complete change throughout the world. Curing this disease became a significant challenge yet. Big Data and data analytics through the COVID-19 data have predicted and found the recovery and mortality rate in many hospitals of many countries. The aim of this paper is discussed in Section IV by comparing three different data analytic models—logistic regression, Kaplan–Meier analysis and SIR model, used for prediction of COVID-19 using myocardial injury dataset. This paper also has a literature study on big data analytics. It concludes with a favourable result on the SIR model. The challenges so far faced by big data and data analytics add a recommendation for other countries to get involved with big data and data analytics on COVID-19.
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