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Categorizing requirements for enterprise architecture management in big data literature

  • Organizations identified the opportunities of big data analytics to support the business with problem-specific insights through the exploitation of generated data. Sociotechnical 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 complex business and IT architectures. The transformation of an organization’s EA is influenced by big data transformation processes and their data-driven approach on all layers. In this paper, we review big data literature to analyze which requirements for the EA management discipline are proposed. Based on a systematic literature identification, conceptual categories of requirements for EA management are elicited utilizing an inductive category formation. These conceptual categories of requirements constitute a category system that facilitates a new perspective on EA management and fosters the innovation-driven evolution of the EA management. discipline.

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Metadaten
Author of HS ReutlingenKehrer, Stefan; Jugel, Dierk; Zimmermann, Alfred
DOI:https://doi.org/10.1109/EDOCW.2016.7584352
ISBN:978-1-4673-9933-3
Erschienen in:2016 IEEE 20th International Enterprise Distributed Object Computing Workshop (EDOCW), EDOCW 2016, 5. - 9. September 2016, Vienna, Austria
Publisher:IEEE
Place of publication:Piscataway, NJ
Editor:Remco Dijkman
Document Type:Conference Proceeding
Language:English
Year of Publication:2016
Tag:big data transformation; conceptual categories of requirements; enterprise architecture management
Page Number:8
First Page:98
Last Page:105
DDC classes:004 Informatik
Open Access?:Nein
Licence (German):License Logo  Lizenzbedingungen IEEE