Data Science is emerging as a hot new profession and academic discipline. Data Scientist: the Sexiest Job of the 21st Century is the title of a recent Harvard Business Review article. Its authors, Tom Davenport and D. J. Patil, define data scientist as “a high-ranking professional with the training and curiosity to make discoveries in the world of big data, . . . Their sudden appearance on the business scene reflects the fact that companies are now wrestling with information that comes in varieties and volumes never encountered before.” They note that demand for data scientists is racing ahead of supply. People with the necessary skills are scarce, primarily because the discipline is so new that there are no university programs offering data science degrees.
But, the situation is rapidly changing. A number of universities are setting up graduate programs in data science. In New York City alone, for example, NYU has launched a new Center for Data Science which will start offering a Master in Data Science in the Fall of this year. Urban informatics, - the application of data science to urban problems, - is the primary focus of NYU’s new Center for Urban Science and Progress, which will start a masters program in Applied Urban Science and Informatics this Fall as well. Columbia University is starting an Institute for Data Science and Engineering. Similar research and educational programs are being organized in universities around the world.
The emergence of data science is closely intertwined with the explosive growth of big data over the past decade. Davenport and Patil write that: “More than anything, what data scientists do is make discoveries while swimming in data. It’s their preferred method of navigating the world around them. At ease in the digital realm, they are able to bring structure to large quantities of formless data and make analysis possible. They identify rich data sources, join them with other, potentially incomplete data sources, and clean the resulting set. In a competitive landscape where challenges keep changing and data never stop flowing, data scientists help decision makers shift from ad hoc analysis to an ongoing conversation with data.”
Data science goes beyond the use of data mining, business analytics and statistical analysis to look for patterns in large data sets. It is more multidisciplinary in nature. According to Wikipedia: “Data science incorporates varying elements and builds on techniques and theories from many fields, including math, statistics, data engineering, pattern recognition and learning, advanced computing, visualization, uncertainty modeling, data warehousing, and high performance computing with the goal of extracting meaning from data and creating data products.”