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Big Data—Integration and Cleansing Environment for Business Analytics with DICE

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Domain-Specific Conceptual Modeling

Abstract

The paper presents the Data Integration and Cleansing Environment—DICE. Its embedded modeling method supports the data understanding and data preparation phases for business analytics endeavours and subsequently decision-making in business process activities. A prototypical implementation is presented by using an example in the field of campaign management which uses traditional customer data in combination with (big) data about customer sentiments from microblogging platforms.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science, University of Vienna, 1090, Vienna, Austria

    Wilfried Grossmann & Christoph Moser

Authors
  1. Wilfried Grossmann
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  2. Christoph Moser
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Corresponding author

Correspondence to Wilfried Grossmann .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science, Research Group Knowledge Engineering, University of Vienna, Wien, Austria

    Dimitris Karagiannis

  2. Institute of Applied Informatics, Alpen-Adria-Universität Klagenfurt Institute of Applied Informatics, Klagenfurt, Austria

    Heinrich C. Mayr

  3. University of Trento , Trento, Italy

    John Mylopoulos

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Grossmann, W., Moser, C. (2016). Big Data—Integration and Cleansing Environment for Business Analytics with DICE. In: Karagiannis, D., Mayr, H., Mylopoulos, J. (eds) Domain-Specific Conceptual Modeling. Springer, Cham. https://doi.org/10.1007/978-3-319-39417-6_5

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  • DOI: https://doi.org/10.1007/978-3-319-39417-6_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39416-9

  • Online ISBN: 978-3-319-39417-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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