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Big data analytics: A literature review paper
Department of Business Informatics and Operations, German University in Cairo (GUC), Cairo.
Department of Business Informatics and Operations, German University in Cairo (GUC), Cairo.ORCID iD: 0000-0003-4250-4752
2014 (English)In: Advances in data mining: applications and theoretical aspects : 14th Industrial Conference, ICDM 2014, St. Petersburg, Russia, July 16-20, 2014. Proceedings / [ed] Petra Perner, Cham: Encyclopedia of Global Archaeology/Springer Verlag, 2014, p. 214-227Conference paper, Published paper (Refereed)
Abstract [en]

In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets. Furthermore, decision makers need to be able to gain valuable insights from such varied and rapidly changing data, ranging from daily transactions to customer interactions and social network data. Such value can be provided using big data analytics, which is the application of advanced analytics techniques on big data. This paper aims to analyze some of the different analytics methods and tools which can be applied to big data, as well as the opportunities provided by the application of big data analytics in various decision domains. © 2014 Springer International Publishing Switzerland.

Place, publisher, year, edition, pages
Cham: Encyclopedia of Global Archaeology/Springer Verlag, 2014. p. 214-227
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 8557
Keyword [en]
analytics, big data, data mining, decision making
National Category
Information Systems, Social aspects
Research subject
Information systems
Identifiers
URN: urn:nbn:se:ltu:diva-27993DOI: 10.1007/978-3-319-08976-8_16Scopus ID: 84905455335Local ID: 1a0d083b-8cd0-45ee-8e1a-7f9325a78fcbISBN: 978-3-319-08976-8-16 (print)OAI: oai:DiVA.org:ltu-27993DiVA, id: diva2:1001185
Conference
Industrial Conference on Advances in Data Mining : Applications and Theoretical Aspects 16/07/2014 - 20/07/2014
Note

Upprättat; 2014; 20150617 (ahmelr)

Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved

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Publisher's full textScopushttp://link.springer.com/chapter/10.1007/978-3-319-08976-8_16

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CiteExportLink to record
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