1. ZHAW digitalcollection
  2. School of Engineering
  3. Publikationen
  4. Publikationen School of Engineering
Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-17427
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBraschler, Martin-
dc.contributor.authorStadelmann, Thilo-
dc.contributor.authorStockinger, Kurt-
dc.date.accessioned2019-07-04T12:53:42Z-
dc.date.available2019-07-04T12:53:42Z-
dc.date.issued2019-06-14-
dc.identifier.isbn978-3-030-11821-1de_CH
dc.identifier.isbn978-3-030-11820-4de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/17427-
dc.description.abstractEven though it has only entered public perception relatively recently, the term "data science" already means many things to many people. This chapter explores both top-down and bottom-up views on the field, on the basis of which we define data science as "a unique blend of principles and methods from analytics, engineering, entrepreneurship and communication that aim at generating value from the data itself". The chapter then discusses the disciplines that contribute to this "blend", briefly outlining their contributions and giving pointers for readers interested in exploring their backgrounds further.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofApplied data science : lessons learned for the data-driven businessde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectData sciencede_CH
dc.subjectAnalyticsde_CH
dc.subjectEngineeringde_CH
dc.subjectEntrepreneurshipde_CH
dc.subjectCommunicationde_CH
dc.subjectDefinitionde_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.titleData sciencede_CH
dc.typeBuchbeitragde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
zhaw.publisher.placeChamde_CH
dc.identifier.doi10.1007/978-3-030-11821-1_2de_CH
dc.identifier.doi10.21256/zhaw-17427-
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end29de_CH
zhaw.pages.start17de_CH
zhaw.parentwork.editorBraschler, Martin-
zhaw.parentwork.editorStadelmann, Thilo-
zhaw.parentwork.editorStockinger, Kurt-
zhaw.publication.statussubmittedVersionde_CH
zhaw.publication.reviewEditorial reviewde_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedInformation Engineeringde_CH
zhaw.webfeedZHAW digitalde_CH
zhaw.webfeedMachine Perception and Cognitionde_CH
zhaw.author.additionalNode_CH
Appears in collections:Publikationen School of Engineering

Files in This Item:
File Description SizeFormat 
ADS_2019_DataScience.pdfPreprint312.32 kBAdobe PDFThumbnail
View/Open
Show simple item record
Braschler, M., Stadelmann, T., & Stockinger, K. (2019). Data science. In M. Braschler, T. Stadelmann, & K. Stockinger (Eds.), Applied data science : lessons learned for the data-driven business (pp. 17–29). Springer. https://doi.org/10.1007/978-3-030-11821-1_2
Braschler, M., Stadelmann, T. and Stockinger, K. (2019) ‘Data science’, in M. Braschler, T. Stadelmann, and K. Stockinger (eds) Applied data science : lessons learned for the data-driven business. Cham: Springer, pp. 17–29. Available at: https://doi.org/10.1007/978-3-030-11821-1_2.
M. Braschler, T. Stadelmann, and K. Stockinger, “Data science,” in Applied data science : lessons learned for the data-driven business, M. Braschler, T. Stadelmann, and K. Stockinger, Eds. Cham: Springer, 2019, pp. 17–29. doi: 10.1007/978-3-030-11821-1_2.
BRASCHLER, Martin, Thilo STADELMANN und Kurt STOCKINGER, 2019. Data science. In: Martin BRASCHLER, Thilo STADELMANN und Kurt STOCKINGER (Hrsg.), Applied data science : lessons learned for the data-driven business. Cham: Springer. S. 17–29. ISBN 978-3-030-11821-1
Braschler, Martin, Thilo Stadelmann, and Kurt Stockinger. 2019. “Data Science.” In Applied Data Science : Lessons Learned for the Data-Driven Business, edited by Martin Braschler, Thilo Stadelmann, and Kurt Stockinger, 17–29. Cham: Springer. https://doi.org/10.1007/978-3-030-11821-1_2.
Braschler, Martin, et al. “Data Science.” Applied Data Science : Lessons Learned for the Data-Driven Business, edited by Martin Braschler et al., Springer, 2019, pp. 17–29, https://doi.org/10.1007/978-3-030-11821-1_2.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.