Data science

from Wikipedia, the free encyclopedia

Data Science (from English data “data” and science “science”, in German also data science ) generally refers to the extraction of knowledge from data.

Data science is an interdisciplinary field of science that enables scientifically sound methods, processes, algorithms and systems to extract knowledge, patterns and conclusions from both structured and unstructured data.

The Data Science degree uses techniques and theories from the fields of mathematics, statistics and information technology, including signal processing , uses probability models from machine learning , statistical learning, programming , data engineering, pattern recognition , forecasting , modeling of uncertainties and data storage .

Persons working in the field of data science are called Data Scientist or data scientists called, with most specialized or specializations of other, higher-level job titles are common (eg. As statisticians, computer scientists).

history

The term "data science" has existed for over 40 years and was originally used by Peter Naur in 1960 to replace the term "computer science" . In 1974 Naur published a survey on contemporary data processing in the Concise Survey of Computer Methods , in which the term "data science" was freely used.

In 1996 the members of the International Federation of Classification Societies (IFCS) met in Kobe for their biennial conference. At this conference, the term “data science” was included in the conference title for the first time.

The modern definition of data science was first drafted during the second Japanese-French statistical symposium at the University of Montpellier II (France) in 1992. The participants recognized the emergence of a new discipline with a special focus on data from different origins, dimensions, types and structures. They shaped the outline of this new science, based on established concepts and principles of statistics and data analysis, making extensive use of the increasing power of computer tools.

In November 1997, CF Jeff Wu gave the keynote address, "Statistics = Data Science?" For his appointment as HC Carver Professor of Statistics at the University of Michigan . In this lecture he characterized statistical work as a trilogy of data acquisition, data modeling and analysis, and decision making. Finally, he created the term "data science" and advocated renaming statistics to "data science" and statisticians to "data scientists". He later presented a lecture entitled "Statistics = Data Science?", The first of his Mahalanobis Memorial Lectures. These lectures honor Prasanta Chandra Mahalanobis , an Indian scientist, statistician and founder of the Indian Statistical Institute.

In 2001, William S. Cleveland introduced data science as a separate discipline in his article "Data Science: An Action Plan for Expanding the Technical Areas of the Field of Statistics". In his report, Cleveland introduced six broad areas of data science for him: multidisciplinary studies, models and methods for data, computing with data, pedagogy, tool assessment and theory.

In April 2002, the International Council for Science: Committee on Data for Science and Theory published the Data Science Journal, which focused on issues such as the description of data systems, their publication on the Internet, applications, and legal issues.

Shortly thereafter, Columbia University began to publish the journal "The Journal of Data Science" in 2003, which provided a platform for all data providers to present their views and ideas for exchange. Much of the journal was devoted to the application of statistical methods and quantitative research.

In 2005 the National Science Board published the report "Long-lived Digital Data Collections: Enabling Research and Education in the 21st Century", in which various experts are listed under the heading Data Scientists who are of crucial importance for the successful management of digital data. Computer scientists, database experts , programmers, domain experts, librarians , archivists and experts in software engineering are named. As part of the responsibilities of data scientists, the development of innovative concepts in the areas of database technology and information science is particularly emphasized. This also includes methods of information visualization , data analysis and knowledge discovery in databases.

The professional field

There is a global shortage of experts in the field of data analysis.

conditions

A data scientist should be convincing and creative, but also have a certain talent for communication in order to be able to exchange ideas with different levels of an organization. He is the link and mediator between all levels of a company and thus assumes the role of the "translator" by making the results just as understandable for the individual departments as for top management. In addition, a data scientist should be open-minded enough to research and use new analysis tools and innovative analysis methods. A data scientist should want to look for other approaches impartially and always ask new questions. This job also requires a certain talent for coordination, not least because certain tasks, such as the acquisition of data, can be delegated to other employees. However, control and management should always remain in the hands of the data scientist.

Area of ​​responsibility

The job of a data scientist is to generate information from large amounts of data and to derive recommendations for action that enable the company to work more efficiently. To do this, he uses innovative analysis tools and develops queries that distill valuable information from confusing amounts of data. Subsequently, hypotheses are derived, which are statistically checked and prepared for management as a basis for decision-making.

Training opportunities

In the German-speaking area, various universities in the German-speaking area offer courses specializing in data science. The focus is on master’s courses, but now bachelor’s courses are also offered. In addition, there are specialized training opportunities and part-time courses.

Bachelor courses: The Technical University of Dortmund has been offering the bachelor course in data analysis and data management since the winter semester 2002/2003. The University of Marburg and the University of Stuttgart offer from the winter semester 2016/2017 the Germany's first bachelor degree programs called data science at. The Technical University OWL in Lemgo offers the bachelor's degree in Data Science, which can also be completed as a dual degree . The University of Applied Sciences Europe -BiTS and BTK offers the Bachelor's degree in Digital Business & Data Science . The Georg-August-University Göttingen offers from the winter semester 2018/2019 at the bachelor programs Applied Data Science and Mathematical data science. At the West Saxon University of Applied Sciences in Zwickau , a bachelor's degree in data science will be offered for the first time in the new federal states from the 2018/2019 winter semester. The Mittweida University of Applied Sciences , which is also located in Saxony, has introduced a specialization of the same name in its bachelor's degree in industrial engineering. At Stralsund University of Applied Sciences , data science has been an integral part of teaching in the business informatics course since 2015 .

Master’s degree courses: The Philipps University of Marburg offers a master’s degree in Data Science in addition to the Bachelor’s degree . At the University of Applied Sciences Berlin , a course is offered in the winter term 2016/17, which dedicates itself, together with the project management this focus. The Hochschule Darmstadt offers from the winter semester 2016/2017 a master's degree data science to which is operated jointly by the departments of computer science and mathematics and science. A master's degree in data science is offered at the Ludwig Maximilians University in Munich , which is funded by the Bavarian Elite Network . The Master's degree in Management & Data Science is offered at the Leuphana University of Lüneburg . The University of Linz offers a business informatics course with a focus on Business Intelligence & Data Science . The Technical University of Dortmund has offered a master's degree in data science since the 2002/2003 winter semester . The Otto von Guericke University Magdeburg offers a master's degree in Data and Knowledge Engineering . The Master's degree in Computational and Data Science is taught at the Friedrich Schiller University Jena . At the Beuth University of Applied Sciences in Berlin, there is an English-language Master's in Data Science with the goal of data science or data engineering. The Paris Lodron University of Salzburg is the first Austrian university to offer the four-semester Master's degree in Data Science from the 2016 winter semester . In 2016 the University of Mannheim presented the Data Science course as its latest addition. Since the 2017/2018 winter semester, the University of Applied Sciences for Technology, Business and Media Offenburg has been offering a master's degree in computer science with a focus on data science & analytics . The RWTH Aachen University offers an English master program data science at.

Doctoral programs: In parallel to the introduction of the Master’s program in Data Science , the Paris Lodron University of Salzburg has set up the doctoral program Statistics and Applied Data Science and will also offer the opportunity to do a doctorate in data science from the winter semester 2016. Depending on the topic of the dissertation, doctoral candidates can acquire a doctorate in the natural sciences or in the technical sciences.

Extra-occupational degree programs and further training opportunities: The Albstadt-Sigmaringen University of Applied Sciences has been offering the first part-time master’s degree in data science in German-speaking countries since October 2015. The Stuttgart Media University offers a further part-time master’s degree in data science and business analytics . The Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS) also offers training courses for data scientists. The EMC Academic Alliance offers a Data Science and Big Data Analytics curriculum . The Technical University of Brandenburg , together with the AWW e. V. offers a further education certificate course "Data Science".

Industry sectors

Large amounts of data are evaluated in all industries today. The lack of data scientists makes it difficult for companies to use the data properly and to draw concrete insights from it. Data is traded as the "new gold". In addition, the market for specialists who can handle data architectures and data models is almost non-existent.

More and more data scientists will also be sought in the logistics industry in the future.

Another industry is the health industry. Through the precise analysis of data from a hospital stay, individualized treatments ( personalized medicine ) could be derived from patient data through similarity analyzes and medication plans could be optimized.

In the retail industry, people's buying behavior can be analyzed in order to work out the causes of returns in the further course. In this way, the number of goods returned can be reduced.

See also

literature

  • Maren Lübcke, Klaus Wannemacher : Teaching data skills at universities: courses in the field of data science . HIS-HE, Hanover 2018. URL: his-he.de (PDF)
  • Cathy O'Neil, Rachel Schutt: Doing Data Science: Straight Talk from the Frontline . O'Reilly 2013. ISBN 1449358659 .
  • John W. Tukey (1962): The future of data analysis . Annals of Mathematical Statistics, Vol. 33, pp. 1-67.
  • John D. Kelleher, Brendan Tierney: Data Science , The MIT Press Essential Knowledge Series, The MIT Press 2018, ISBN 9780262535434
  • Johannes Kröckel: Data Analytics in Production and Logistics . Vogel Communications Group 2019. ISBN 978-3-8343-3419-0 .

Web links

Individual evidence

  1. ↑ Dhar, V. (2013): Data science and prediction . Communications of the ACM 56 (12): 64. doi : 10.1145 / 2500499
  2. ↑ Jeff Leek (December 12, 2013): The key word in "Data Science" is not Data, it is Science . Simply Statistics.
  3. ↑ Vasant Dhar: Data Science and Prediction | December 2013 | Communications of the ACM. Retrieved June 19, 2018 .
  4. ^ The key word in "Data Science" is not Data, it is Science · Simply Statistics. Accessed June 19, 2018 .
  5. ^ Forbes, Gil Press: A Very Short History of Data Science . May 2013 (English).
  6. ↑ Escoufier et al, editors. Preface . In: Data Science and its Application ( English ). Academic Press, Tokyo 1995, ISBN 0-12-241770-4 .
  7. ↑ a b Wu, CFJ (1997): Statistics = Data Science? . Retrieved October 9, 2014.
  8. ^ Identity of statistics in science examined . The University Records, Nov. 9, 1997, The University of Michigan. Retrieved August 12, 2013.
  9. ^ PC Mahalanobis Memorial Lectures, 7th series . PC Mahalanobis Memorial Lectures, Indian Statistical Institute. Retrieved August 18, 2013.
  10. ↑ Data Science Journal. (2012, April). Available volumes. Retrieved from Japan Science and Technology Information Aggregator, Electronic: online ( Memento of the original from April 3, 2012 in the Internet Archive ) Info: The archive link was automatically inserted and not yet checked. Please check the original and archive link according to the instructions and then remove this notice. @1@ 2Template: Webachiv / IABot / www.jstage.jst.go.jp
  11. ↑ Data Science Journal. (2002, April). Contents of Volume 1, Issue 1, April 2002. Retrieved from Japan Science and Technology Information Aggregator, Electronic: online
  12. ^ The Journal of Data Science. (2003, January). Contents of Volume 1, Issue 1, January 2003. Retrieved from http://www.jds-online.com/v1-1
  13. ^ National Science Board: Long-Lived Digital Data Collections Enabling Research and Education in the 21st Century , National Science Foundation, accessed July 7, 2016.
  14. ↑ Great demand for data scientists , derStandard.at of February 26, 2015, accessed on February 28, 2015.
  15. ↑ Dream job data scientist , statista.com from February 19, 2015, accessed on February 28, 2015.
  16. ↑ Data Scientists - The Most Coveted All-Rounders of the 21st Century , capgemini.com from January 20, 2014, accessed on February 28, 2015.
  17. ↑ Faculty of Statistics - Bachelor of Data Analysis and Data Management. Retrieved September 14, 2018 (German).
  18. ↑ University of Stuttgart, Department of Computer Science - Data Science. Retrieved July 4, 2016 .
  19. ^ A b Philipps University of Marburg, Department of Mathematics and Computer Science - Degree Programs. Retrieved June 13, 2016 .
  20. ↑ Technical University of Ostwestfalen-Lippe, Department of Electrical Engineering and Technical Computer Science. Retrieved March 20, 2018 .
  21. ↑ Bachelor's degree in Digital Business & Data Science (B.Sc.). In: University of Applied Sciences Europe - Iserlohn · Berlin · Hamburg. Retrieved May 7, 2018 .
  22. ↑ Georg-August-Universität Göttingen - Public Relations: Applied Data Science (B.Sc.) - Georg-August-Universität Göttingen. Retrieved April 27, 2018 .
  23. ^ Georg-August-Universität Göttingen - Public Relations: Mathematical Data Science (B.Sc.) - Georg-August-Universität Göttingen. Retrieved April 27, 2018 .
  24. ↑ University of Applied Sciences Mittweida, Faculty of Industrial Engineering: Industrial Engineering (Bachelor). Retrieved February 20, 2020 .
  25. ↑ Bachelor of Business Informatics - Stralsund University. Retrieved June 12, 2020 .
  26. ↑ HTW Berlin: Project Management & Data Science . Retrieved March 11, 2016.
  27. ↑ Darmstadt University of Applied Sciences, FB I and FB MN: Master's degree in Data Science . Retrieved April 28, 2016.
  28. ↑ Data Science (Master). August 10, 2016, accessed November 22, 2016 .
  29. ↑ New master's degree in Data Science , at www.uni-muenchen.de
  30. ^ Leuphana University Lüneburg: Management & Data Science . Retrieved February 28, 2015.
  31. ↑ Data Science as a new course at the University of Linz , futurezone from August 19, 2014, accessed on February 28, 2015.
  32. ↑ Technical University of Dortmund - Master's degree in Datascience . Retrieved February 28, 2015.
  33. ^ Otto von Guericke University Magdeburg - Data and Knowledge Engineering . Retrieved February 28, 2015.
  34. ↑ Friedrich Schiller University Jena - Master's degree in Computational and Data Science . Retrieved February 28, 2015.
  35. ↑ Data Science Beuth University. Retrieved May 31, 2017 .
  36. ↑ APA - First Master's degree in Data Science starts in Salzburg . Retrieved September 12, 2016.
  37. ↑ a b University of Salzburg - Data Science . Retrieved September 12, 2016.
  38. ↑ Computer Science Master - Course of Studies. Offenburg University , accessed on July 27, 2018 .
  39. ↑ RWTH Aachen University: Data Science M.Sc. - RWTH AACHEN UNIVERSITY - German. Retrieved November 12, 2018 .
  40. ↑ Albstadt-Sigmaringen University of Applied Sciences - Data Science course . Retrieved June 11, 2015.
  41. ↑ Stuttgart Media University - Data Science . Retrieved July 1, 2016.
  42. ↑ Fraunhofer Institute for Intelligent Analysis and Information Systems - Data Scientist Training . Retrieved February 28, 2015.
  43. ↑ Certificate course "Data Science (FH)". In: Brandenburg University of Applied Sciences . Brandenburg University of Applied Sciences, August 13, 2015, accessed on September 3, 2015 .