Big data analytics is a process of examining, cleaning, transforming, and modeling large sets of data to discover useful information and support decision-making. In healthcare, it can be used to improve patient outcomes by identifying patterns and trends in patient data, reducing unnecessary costs and identifying new drug targets. The use of big data analytics can play a critical role in improving the quality, accessibility, and affordability of healthcare for people around the world. In terms of pandemics like COVID-19, big data analytics can play a significant role in early detection and prevention of pandemics like COVID-19. By analyzing large amounts of data from various sources such as social media, electronic health records, and surveillance systems, patterns and trends can be identified that may indicate the emergence of a new disease. This information can then be used to quickly identify and track outbreaks, as well as to develop targeted prevention and control measures. Big data analytics can help detect and prevent by analyzing data on factors that contribute to the spread of a disease, using various algorithms like machine learning, network analysis algorithms, GLEAM algorithm, NLP algorithm etc. and using data visualization tools to present the results.
Key words: NLP, Big data, GLEAM, COVID-19.
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