In today’s digital world, information is growing along with the expansion of Internet usage worldwide. As a consequence, bulk of data is generated constantly which is known to be “Big Data”. One of the most evolving technologies in twenty-first century is Big Data analytics, it is promising field for extracting knowledge from very large datasets and enhancing benefits while lowering costs. Due to the enormous success of big data analytics, the healthcare sector is increasingly shifting toward adopting these approaches to diagnose diseases. Due to the recent boom in medical big data and the development of computational methods, researchers and practitioners have gained the ability to mine and visualize medical big data on a larger scale. Thus, with the aid of integration of big data analytics in healthcare sectors, precise medical data analysis is now feasible with early sickness detection, health status monitoring, patient treatment, and community services is now achievable. With all these improvements, a deadly disease COVID is considered in this comprehensive review with the intention of offering remedies utilizing big data analytics. The use of big data applications is vital to managing pandemic conditions, such as predicting outbreaks of COVID-19 and identifying cases and patterns of spread of COVID-19. Research is still being done on leveraging big data analytics to forecast COVID-19. But precise and early identification of COVID disease is still lacking due to the volume of medical records like dissimilar medical imaging modalities. Meanwhile, Digital imaging has now become essential to COVID diagnosis, but the main challenge is the storage of massive volumes of data. Taking these limitations into account, a comprehensive analysis is presented in the systematic literature review (SLR) to provide a deeper understanding of big data in the field of COVID-19.

在当今的数字世界中，信息随着全球互联网使用的扩展而不断增长。因此，大量数据不断产生，被称为“大数据”。大数据分析是二十一世纪最发展的技术之一，它是从非常大的数据集中提取知识并在降低成本的同时提高效益的有前景的领域。由于大数据分析的巨大成功，医疗保健行业越来越多地转向采用这些方法来诊断疾病。由于近年来医疗大数据的蓬勃发展和计算方法的发展，研究人员和从业者已经获得了更大规模地挖掘和可视化医疗大数据的能力。因此，借助大数据分析在医疗保健领域的整合，可以实现精确的医疗数据分析，实现早期疾病检测、健康状况监测、患者治疗和社区服务。通过所有这些改进，本次全面审查将致命疾病新冠肺炎视为一种疾病，旨在利用大数据分析提供补救措施。大数据应用程序的使用对于管理大流行病至关重要，例如预测 COVID-19 的爆发以及识别 COVID-19 的病例和传播模式。利用大数据分析来预测 COVID-19 的研究仍在进行中。但由于医疗记录数量巨大（例如医学成像方式不同），仍然缺乏对新冠病毒疾病的准确和早期识别。与此同时，数字成像现已成为新冠诊断的关键，但主要挑战是海量数据的存储。考虑到这些局限性，系统文献综述（SLR）中提出了全面的分析，以更深入地了解 COVID-19 领域的大数据。