The year 2020 will be written in the history as the year that has caused catastrophic impact on health, human lives, and most importantly the economy that has been rumbled in some countries to the levels of World War I and II. This pandemic also exposed the loopholes in the systems for few 'Developed Nations', 'Established Public Health Systems', and 'Billion Dollar Forex Reserves' that most of the countries relied upon in general. All these were challenged to the core once the COVID-19 pandemic started growing exponentially from March 2020 forcing the countries to go under lockdown which has curved down their economic charts. Malaysia too has suffered with a months-long lockdown, growing unemployment and shrinking economy. The SMEs in Malaysia are among the worst affected. In May 2020, almost 50 of the SMEs reached a position where their very existence was at stake. A potential second or third wave of COVID-19 or some other pandemic in future is not any surprise for Malaysia. But, how far the country and its SMEs are prepared to face such situation again is the question. A quick and accurate data analytics on historical pandemics, hospital data, infection rates, tracking, testing and treatments offered may help in predicting the primary signs that can protect from disasters to a great extent. This study applies 'technology acceptance model' to Malaysian SMEs to explore the possibility of Data Science in launching accurate forecasts that could keep them in a better position rather than getting caught in surprise lockdowns. Since the acceleration in the spread of infectious diseases lately around the globe is due to the growth in the human population and globalisation, Data Analytics can be used to predict where the potential outbreaks may unfold next and thereby to flag the early alert. © 2020 IEEE.