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A systematic literature review of big data literature for EA evolution

  • Many organizations identified the opportunities of big data analytics to support the business with problem-specific insights through the exploitation of generated data. Socio-technical solutions are developed in big data projects to reach competitive advantage. Although these projects are aligned to specific business needs, common architectural challenges are not addressed in a comprehensive manner. Enterprise architecture management is a holistic approach to tackle the complex business and IT architecture. The transformation of an organization's EA is influenced by big data projects and their data-driven approach on all layers. To enable strategy­ oriented development of the EA it is essential to synchronize these projects supported by EA management. In this paper, we conduct a systematic review of big data literature to analyze which requirements for the EA management discipline are proposed. Thereby, a broad overview about existing research is presented to facilitate a more detailed exploration and to foster the evolution o the EA management discipline.

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Name:Kehrer, Stefan; Jugel, Dierk; Zimmermann, Alfred
Erschienen in:Digital Enterprise Computing (DEC 2016) : Böblingen, Germany, June 14 - 15, 2016
Publisher:Gesellschaft für Informatik
Place of publication:Bonn
Editor:Dieter Hertweck
Document Type:Part of a Book
Year of Publication:2016
Tag:EA evolution; big data management; big data projects; enterprise architecture; enterprise architecture management
First Page:209
Last Page:220
Catalogue entry:Im Katalog der Hochschule Reutlingen ansehen
Dewey Decimal Classification:004 Informatik
Open Access:Ja
Licence (German):License Logo  Open Access