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International Conference on Conceptual Modeling

ER 2014: Advances in Conceptual Modeling pp 75–84Cite as

Business Intelligence and Big Data in the Cloud: Opportunities for Design-Science Researchers

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8823))

Abstract

Cloud computing and big data offer new opportunities for business intelligence (BI) and analytics. However, traditional techniques, models, and methods must be redefined to provide decision makers with service of data analysis through the cloud and from big data. This situation creates opportunities for research and more specifically for design-science research. In this paper, we propose a typology of artifacts potentially produced by researchers in design science. Then, we analyze the state of the art through this typology. Finally, we use the typology to sketch opportunities of new research to improve BI and analytics capabilities in the cloud and from big data.

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Author information

Authors and Affiliations

  1. CEDRIC-CNAM, Paris, France

    Odette Mwilu Sangupamba & Isabelle Comyn-Wattiau

  2. ESSEC Business School, Cergy-Pontoise, France

    Nicolas Prat & Isabelle Comyn-Wattiau

Authors
  1. Odette Mwilu Sangupamba
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  2. Nicolas Prat
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  3. Isabelle Comyn-Wattiau
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Editor information

Editors and Affiliations

  1. UQ Business School, The University of Queensland, 4072, St Lucia, QLD, Australia

    Marta Indulska

  2. 316B Information Sciences and Technology Building, Penn State University, 16802, University Park, PA, USA

    Sandeep Purao

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© 2014 Springer International Publishing Switzerland

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Sangupamba, O.M., Prat, N., Comyn-Wattiau, I. (2014). Business Intelligence and Big Data in the Cloud: Opportunities for Design-Science Researchers. In: Indulska, M., Purao, S. (eds) Advances in Conceptual Modeling. ER 2014. Lecture Notes in Computer Science, vol 8823. Springer, Cham. https://doi.org/10.1007/978-3-319-12256-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-12256-4_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12255-7

  • Online ISBN: 978-3-319-12256-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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