Big Data Analysis on COVID-19

Authors

  • Vinay Kailash Upadhyay Department of Computer science & Engineering, Shri Sant Gadge Baba College of Engineering and Technology, Bhusawal, INDIA
  • Dr. Dinesh Dattatray Patil Associate Professor and Head, Department of Computer science & Engineering, Shri Sant Gadge Baba College of Engineering and Technology, Bhusawal, INDIA
  • Prof. Yogesh Patil Assistant Professor, Department of Computer science & Engineering, Shri Sant Gadge Baba College of Engineering and Technology, Bhusawal, INDIA

DOI:

https://doi.org/10.31033/ijemr.12.4.19

Keywords:

Big Data Analytics, COVID-19, Health Science

Abstract

Over the past 2 years, the Coronavirus has rapidly spread to all parts of the world. Scientist and researchers are continuing their research to find a permanent cure. As the number of cases are increasing, so the tests are for Coronavirus is increasing rapidly, it is impossible to maintain data of test due to the time and cost factors. Big data is very helpful to maintain the track record of the COVID-19 infected patients in a very systematic way and will reduce the time delay for the results of the medical tests and modulate doctors to give proper medical treatment to the infected person. Big data analytics play an important role in building knowledge, studies required in making decisions and precautionary measures. However, due to the vast amount of data available on COVID-19 from various sources, there is a need to review the roles of big data analysis in controlling and tracking the spread of COVID-19, presenting the main challenges and directions of COVID-19 data analysis, as well as providing a framework on the related existing applications and studies to facilitate future research on COVID-19 analysis. Keywords-big data analytics, 2019 novel coronavirus disease (COVID-19).

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Published

2022-08-31

How to Cite

Vinay Kailash Upadhyay, Dr. Dinesh Dattatray Patil, & Prof. Yogesh Patil. (2022). Big Data Analysis on COVID-19. International Journal of Engineering and Management Research, 12(4), 165–169. https://doi.org/10.31033/ijemr.12.4.19

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