A Brief History of Data Science Pt.3
History is an important teacher. It can remind us of where we came from and offer insights into how we can improve our past processes. It is important that we look back on history often, if only for a few moments. That is precisely why I have created this series of blogs. In this third entry, I will continue to take a quick glance back at the history of data science.
1997: This was an interesting year for the industry, as we saw our first glimpses of the push to change the industry’s name from “statistics” to “data science.” Professor C.F. Jeff Wu said as much during his opening statement for the H.C. Carver Chair in Statistics at the University of Michigan. Wu also made a push for statisticians to be called data scientists.
2007: History is made at Fudan University in Shanghai, China as the Research Center for Dataology and Data Science is created. Two years later, two of the center’s researchers publish one of their most prized works: “Introduction to Dataology an Data Science.” The journal provides an overview of what data science is, and how it differs from other, more traditional branches of science. The center is still important to this day, as it holds annual meetings and conferences on data science.
2009: Google’s Chief Economist at the time, Hal Varian, makes a bold statement in the McKinsey Quarterly, stating that statisticians, or data scientists, will be the job of the future. The role of data scientists, as he puts it, will be the, “sexy job in the next ten years.”
2009-2011: During these few years, multiple data scientists, all of whom are respected figures in the industry, offer their insights and thoughts on the industry, where it is headed, and what it all means. In 2009, Mike Driscoll explains what data scientists will need to know in order to become successful in the future; in 2010, Kenneth Cukier simply reminds us of the data scientist’s rise to fame; and in 2011, David Smith tries to make sense of the term “data scientist” and how it differs from “statistician.” Throughout this period, many of these scholars simply seemed to struggle with their new term, their “new” industry and the sudden high demand for their expertise. It was an interesting time for data science in which individuals were gripping with their identities.
Data science has had an interesting history thus far, and it is still being written every day. As demand for the industry continues to grow, we will undoubtedly have much to look back in the future, but until then, let us look back on our past and learn from our successes and our mistakes.