  COVID 19 is an acute disease that started spreading throughout the world,
beginning in December 2019. It has spread worldwide and has affected more than
7 million people, and 200 thousand people have died due to this infection as of
Oct 2020. In this paper, we have forecasted the number of deaths and the
confirmed cases in Los Angeles and New York of the United States using the
traditional and Big Data platforms based on the Times Series: ARIMA and ETS. We
also implemented a more sophisticated time-series forecast model using Facebook
Prophet API. Furthermore, we developed the classification models: Logistic
Regression and Random Forest regression to show that the Weather does not
affect the number of the confirmed cases. The models are built and run in
legacy systems (Azure ML Studio) and Big Data systems (Oracle Cloud and
Databricks). Besides, we present the accuracy of the models.
