About a year ago, an article in the Harvard Business Review called data scientists the sexiest job of the 21st century. Its authors, Tom Davenport and D. J. Patil, succinctly defined data scientist as “a high-ranking professional with the training and curiosity to make discoveries in the world of big data.”
For over ten years, we’ve been using the term big data to refer to the fast growing volumes and varieties of digital data being collected, much of it in real-time. Over the years, we’ve made considerable progress in the storage and management of these big data sets, helped along by major advances in computer science, math, statistics and related disciplines.
But all that progress is of limited value without people with the skill sets to extract important insights out of all that data. The promise of data science is that big data will lead to significantly better decisions and predictions, to the smart management of social organizations like cities, companies and economies, and to research breakthroughs in the social sciences, medicine and a number of other disciplines. And, on that front, most everyone agrees that people with the necessary skills are scarce. Demand for data scientists has raced ahead of supply, primarily because there have been few university programs training students in this emerging discipline.
But, the situation is rapidly changing. A recent NY Times article observed that “Universities can hardly turn out data scientists fast enough. . . Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.”