Data science

Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processing, scientific visualization, algorithms, coding (like Python, SQL, and R), and systems to extract or extrapolate knowledge from potentially noisy, structured, or unstructured data. A data scientist is a professional who creates programming code and combines it with statistical knowledge to summarize data.

Scope of data science

Data science plays a critical role in modern decision-making by enabling organizations to extract actionable insights from large and complex datasets.

Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.

Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is distinct from computer science and information science. Turing Award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational, and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge.

Data science is often described as a multidisciplinary and rapidly evolving field because it draws on techniques from diverse areas, such as computer science, statistics, information science, and other subject-specific disciplines.