Thomas H. Davenport is an academic and author specializing in analytics, business process innovation and knowledge management. He is currently the President’s Distinguished Professor in Information Technology and Management at Babson College, Director of Research at the International Institute for Analytics, and a Senior Advisor to Deloitte Analytics.
We live in a world awash with data. Data is proliferating at an astonishing rate—we have more and more data all the time, and much of it was collected in order to improve decisions about some aspect of business, government, or society. If we can’t turn that data into better decision making through quantitative analysis, we are both wasting data and probably creating suboptimal performance.
— Tom Davenport
Stephen Jay Gould (September 10, 1941 – May 20, 2002) was an American paleontologist, evolutionary biologist, and historian of science. He was also one of the most influential and widely read writers of popular science of his generation. Gould spent most of his career teaching at Harvard University and working at the American Museum of Natural History in New York. In the later years of his life, Gould also taught biology and evolution at New York University.
Facts and theories are different things, not rungs in a hierarchy of increasing certainty. Facts are the world’s data. Theories are structures of ideas that explain and interpret facts. Facts do not go away while scientists debate rival theories for explaining them. Einstein’s theory of gravitation replaced Newton’s, but apples did not suspend themselves in mid-air pending the outcome.
— Stephen Jay Gould
John Tukey (1915-2000) was an American mathematician and has been called the father of modern exploratory data analysis and data visualization. Tukey has written a lot on these subject, so I thought I’d share three of my favorite and also more popular quotes:
The data may not contain the answer. The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.
To statisticians, hubris should mean the kind of pride that fosters an inflated idea of one’s powers and thereby keeps one from being more than marginally helpful to others. … The feeling of “Give me (or more likely even, give my assistant) the data, and I will tell you what the real answer is!” is one we must all fight against again and again, and yet again.
Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.
So, if you like these quotes and are looking for a great data science read, then check out Tukey’s text, Exploratory Data Analysis.