As with any fairly new term which is closely related to several others, data science means different things to different people. Experts and institutions use broader or narrower definitions and emphasize different aspects of data science. At ASU, data science is an interdisciplinary blend of mathematics, statistics and computer science, which applies scientific methods to extract information and provide an insight from (often large and noisy) data. An estimated shortage of up to 190,000 data analysts in the U.S. is creating high demand for data scientists with the know-how to use data to make effective decisions.
In a broader meaning, data science also includes capturing, preparing and exploring data (getting a first insight, visualizing), prior to applying mathematical and statistical methods on these data.
The relationship between math, statistics and computer science existed decades before “data science” became a new buzzword. Modern technology and increased computer power enabled these three disciplines to use methods that were earlier only theorized and could not be broadly used due to limitations of earlier computers.
More powerful computers enabled automation of collecting huge amounts of data - big data that could not be grasped by humans due to its size. With the help of more powerful computers, the three disciplines developed computationally more demanding new methods, and got blended even more tightly. According to some experts, a new discipline emerged - Data Science.