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Big Data Analytics Assignment: Determining Nature Of Covid-19

s This virus is affecting the economy of many countries. Millions of people globally losing their lives. This can lead to a massive loss for any country [3]. It is vital to analyze the pattern of the disease. Thus, big data is a beneficial technology for this situation. The main research questions are as follows: How can scientists use Big Data to predict the nature and pattern of the disease called COVID-19? Through this central topic, various sub-topics can be questioned. How can the travel history of the citizen be mapped? Why is it necessary to establish an effective health management structure? How to find the number of people entering and leaving the Containment zone? How much will Big Data Analytics be successful in predicting the pattern of the disease? What is the way to identify the nature of disease through various symptoms? How can policymakers differentiate between symptomatic and asymptomatic people? How to record all these data comprehensively? What is possible medical attention required for critical patients? How can Big Data predict the growth of the SARS-COV-2 virus? The researcher took various methodological approach The inductive approach has been chosen to understand all the risk factor and the consequences related to the deadly disease. By using Big data analytics, the inductive approach will evaluate the different observations [4]. Big data tools are helpful to gather all the pieces of information about the outbreaks through these large sets of observations. It uses large sets of algorithms and finally sees the outbreak pattern. The observations evaluated through Big data tools are the spreading pattern of the disease, travel history of citizens of different countries, various symptoms related to COVID-19 etc. [5]. Big data tools show the appropriate result of the analysis. Research Design This research conducted various observations throughout different populations [6]. Also, all required health-related data has been recorded. Researchers have used the primary data collection method. Millions of surveys have been conducted to identify the different perspectives [7]. These large sets of data are analyzed by using the machine learning tool and Big data analytics. Big data holds the purpose for storing health records across the different population. Big data analytics also helps to evaluate the probable research needed in this field. Literature review Big data analytics is a newly developed innovative technology. This sophisticated digital technology has been served the various purpose of the human being [8]. This technology used complex sets of algorithms. This is the era of Industry 4.0. the world is looking for a more advanced sort of digital technology. These big data analytics can predict the future. This ability to give futuristic insights can be used in various sectors like health care sectors [9]. The world is facing the biggest pandemic of the era that COVID- 19. The SARS-COV-2 virus is destroying millions of people’s lives across the world. The zoonotic virus is the deadliest because it transmits from human to human within few minutes. The outbreak of this deadliest virus in the first months of 2020 creates a severe situation [10]. Therefore, this research aims to combine the use of digital technology with the health care departments. It will not only help to mitigate the outbreaks; it will also help to analyze the disease pattern in the near future. The situation becomes even worse when people are moving from one country to another country. Hence, the policymakers have to impose stricter guideline [11]. Several nations imposed nationwide lockdown. The purpose of Big data analytics is quite broad. Firstly, it will help the researchers to identify the potential risk factors. Secondly, handling a large volume of datasets is quite tricky. Another helpful feature is that Big data analytics uses sophisticated algorithms which helps to analyze the future disease pattern. The virus is mutating day by day[12]. The new strains are much deadlier than the previous ones. Hence, this research is very much relevant in this pandemic scenario. References [1] J. A. Shaw, N. Sethi, and C. K. Cassel, “Social license for the use of big data in the COVID-19 era,” npj Digital Medicine. 2020, doi: 10.1038/s41746-020-00342-y. [2] Q. Jia, Y. Guo, G. Wang, and S. J. Barnes, “Big data analytics in the fight against major public health incidents (Including COVID-19): A conceptual framework,” Int. J. Environ. Res. Public Health, 2020, doi: 10.3390/ijerph17176161. [3] J. Wu, J. Wang, S. Nicholas, E. Maitland, and Q. Fan, “Application of big data technology for COVID-19 prevention and control in China: Lessons and recommendations,” J. Med. Internet Res., 2020, doi: 10.2196/21980. [4] C. Zhou et al., “COVID-19: Challenges to GIS with Big Data,” Geogr. Sustain., 2020, doi: 10.1016/j.geosus.2020.03.005. [5] C. M. Chen et al., “Containing COVID-19 among 627,386 persons in contact with the diamond princess cruise ship passengers who disembarked in Taiwan: Big data analytics,” J. Med. Internet Res., 2020, doi: 10.2196/19540. [6] A. Belayneh, “Off-Label Use of Chloroquine and Hydroxychloroquine for COVID-19 Treatment in Africa Against WHO Recommendation,” Res. Rep. Trop. Med., 2020, doi: 10.2147/rrtm.s269936. [7] W. Ming, Z. Zhou, H. Ai, H. Bi, and Y. Zhong, “COVID-19 and Air Quality: Evidence from China,” Emerge. Mark. Finance. Trade, 2020, doi: 10.1080/1540496X.2020.1790353. [8] Pham, Q. V., Nguyen, D. C., Huynh-The, T., Hwang, W. J., & Parthian, P. N. (2020). Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts. IEEE Access. [9] Wu, J., Wang, J., Nicholas, S., Maitland, E., & Fan, Q. (2020). Application of big data technology for COVID-19 prevention and control in China: Lessons and recommendations. Journal of Medical Internet Research. [10] Haleem, A., Javaid, M., Khan, I. H., & Vaishya, R. (2020). Significant Applications of Big Data in COVID-19 Pandemic. Indian Journal of Orthopedics. [11] Zhou, C., Su, F., Pei, T., Zhang, A., Du, Y., Luo, B., … Xiao, H. (2020). COVID-19: Challenges to GIS with Big Data. Geography and Sustainability. [12] Jung, J. H., & Shin, J. I. (2020). Big data analysis of media reports related to COVID-19. International Journal of Environmental Research and Public Health.

Subject Name: Computer Science

Level: Undergraduate

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