What is Data science?
{{Use dmy dates|date=May 2019}} '''Data science''' is the study of the extraction of [[knowledge]] from [[data]]. It uses [[Technique|techniques]] from many fields, including [[signal processing]], [[mathematics]], [[probability]], [[machine learning]], [[computer programming]], [[statistics]], [[data engineering]], [[pattern matching]], and [[data visualization]], with the goal of extracting useful knowledge from the data. With computer systems able to handle more data, [[big data]] is an important aspect of data science. A person that does data science is called a data scientist.<ref>{{Cite web|date=2022-03-26|title=What is a Data Scientist? {{!}} Data Basecamp|url=https://databasecamp.de/en/ml-blog/data-scientists|access-date=2024-09-17|language=en-US}}</ref> Data scientists solve complicated data problems using mathematics, statistics and [[computer science]].<ref>{{cite web|title=Big Careers in Big Data |url=http://www.villanovau.com/university-online-programs/careers-in-big-data/ |publisher=[[Villanova University]]}}</ref> However, a data scientist is most likely to be an expert in only one or two of these disciplines, meaning that [[Interdisciplinarity|cross disciplinary]] teams can be a key component of data science. Good data scientists are able to apply their skills to achieve many kinds of purposes. Their skills and competencies vary widely. == References == {{RefList}} == Further reading == * ''Data Science for Business'' by Foster Provost and Tom Fawcett * ''The Art of Data Science'' by Roger D. Peng and Elizabeth Matsui * ''Machine Learning Yearning'' by Andrew Ng [[Category:Data science| ]] {{sci-stub}}