Data Science

Data science is interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured,[1][2] similar to data mining. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured,[1][2] similar to data mining. Data science is a “concept to unify statistics, data analysis, machine learning and their related methods” in order to “understand and analyze actual phenomena” with data.[3] It employs techniques and theories drawn from many fields within the context of mathematics, statistics, information science, and computer 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.[4][5] In 2012, when Harvard Business Review called it “The Sexiest Job of the 21st Century”,[6] the term “data science” became a buzzword. It is now often used interchangeably with earlier concepts like business analytics,[7] business intelligence, predictive modeling, and Statistics. Even the suggestion that data science is sexy was a paraphrased reference to Dr. Hans Rosling’s 2011 BBC documentary quote, “Statistics, is now the sexiest subject around” [1]. Nate Silver referred to data science as a sexed up term for statistics. In many cases, earlier approaches and solutions are now simply rebranded as “data science” to be more attractive, which can cause the term to become “dilute[d] beyond usefulness.”[9] While many university programs now offer a data science degree, there exists...
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