This survey paper presents a comprehensive overview of two crucial fields - big data analytics algorithms and advanced pandemic viruses. It explores various big data analytics algorithms, including linear regression, logistic regression, K-nearest neighbors, clustering, and classification, elucidating their applications and relevance in different industries. Moreover, it delves into significant pandemic viruses like HIV/AIDS, COVID-19, and Malaria, highlighting their origins, impact on global health, and measures to control their spread. Additionally, the paper examines the intersection between big data analytics and pandemic virus research, emphasizing how data-driven insights can enhance disease surveillance and response strategies. It also identifies future research directions and addresses challenges associated with big data analytics and pandemic virus research. Ultimately, the survey paper advocates for responsible data practices and collaboration to strengthen global health systems and combat emerging infectious diseases effectively.