More than fifty years ago, John Tukey first envisioned a field we now call “Data Science” (he called it “Data Analysis”) to replace academic statistics. George Box, who famously said “all models are wrong”, instead called “Data Analysts [to] get themselves together and become whole Statisticians before it is too late”. Despite their differences, both Tukey and Box relentlessly emphasised on the cycle of statistical research—Conjecture -> Design -> Analysis -> Conjecture -> Design -> Analysis -> …. This talk argues that the problem is not whether we should call something “Statistics” or “Data Science”. The problem is that we should take a holistic view of any statistical research and participate in every part of the cycle. This point will be illustrated by two research problems that the speaker has been working on. One is on the cholesterol hypothesis and the controversial role of HDL cholesterol; the other is on the current novel coronavirus outbreak around the world.