Professor Thomas Davenport of Babson College, Harvard Business School and the MIT Sloan School of Management delivered his keynote address on the history of data analytics at Open Data Science Conference East 2017 in Boston, titled Four Eras of Analytics and Data Science.

Prof. Davenport’s speech covered the span of data analytics from a business perspective, beginning in the 1970s up through modern times, breaking the practice out into four main eras.

The history of data science is extraordinarily brief compared to the long arcs of biology, chemistry, and other disciplines. Nonetheless, this history rich in its own way, drawn from a group of movers and shakers that contrasts sharply with the academics who established the study of the physical world centuries before. Read on to get a sense of how we got from ‘back room’ analysts to the ‘sexiest job of the 21st Century’.

• Era One: Artisanal Analytics
• Era Two: Big Data Analytics
• Era Three: Data Economy Analytics
• Era Four: Autonomous Analytics

Coronavirus Has Upended Everything Airlines Know About Pricing. (WSJ, August, 2020). The pandemic has completely confounded the computers that spit out airfares based on passenger behavior. Part of the problem for airlines is that next year, pricing systems won’t have good data either: 2020 won’t be indicative of 2021, they hope.

“The entire demand patterns and booking patterns have changed. Not only are they lower, but any information about the mix of business and leisure bookings is no longer relevant,” says Peter Belobaba, principal research scientist for air transportation at the Massachusetts Institute of Technology.