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.