The field of Data Science deals with the theories, methodologies and tools of applying statistical concepts and computational techniques to various data analysis problems related to science, engineering, medicine, business, etc. The objective is to inspect, clean, transform and model data in order to discover useful information, suggest conclusions and support decision-making. It is an emerging topic that plays a critical role in almost every discipline of today’s science and technology and has become an indispensable component.

Data science is a highly interdisciplinary field. Data Science methodologies are mostly derived from statistics theories. The computational algorithms for implementing these statistical methodologies are based upon numerical computation and optimization, and are often executed on a large-scale hardware platform composed of massive computing units and storage devices. These kinds of data analyses can be applied to a wide range of specific problems across the natural and social sciences and serve as the foundation for artificial intelligence. Data Science can be extensively applied to economics, biology, health care, quantitative social science including global health and environmental science, and humanities (e.g., digital media). Numerous new applications are being discovered, and established techniques are being applied in new ways to solve emerging problems. Meanwhile, a variety of career opportunities are open to students with appropriate training in interdisciplinary data science.