Business Intelligence

Third European Summer School, eBISS 2013, Dagstuhl Castle, Germany, July 7-12, 2013, Tutorial Lectures

  • Esteban Zimányi
Textbook eBISS 2013

Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 172)

Table of contents

  1. Front Matter
    Pages I-IX
  2. Toon Calders
    Pages 1-32
  3. Wil M.P. van der Aalst
    Pages 33-76
  4. Thomas Neuböck, Bernd Neumayr, Michael Schrefl, Christoph Schütz
    Pages 77-120
  5. Oscar Romero, Alberto Abelló
    Pages 121-149
  6. Ulrike Fischer, Wolfgang Lehner
    Pages 150-181
  7. Artur Wojciechowski, Robert Wrembel
    Pages 182-217
  8. Back Matter
    Pages 243-243

About this book


To large organizations, business intelligence (BI) promises the capability of collecting and analyzing internal and external data to generate knowledge and value, thus providing decision support at the strategic, tactical, and operational levels. BI is now impacted by the “Big Data” phenomena and the evolution of society and users. In particular, BI applications must cope with additional heterogeneous (often Web-based) sources, e.g., from social networks, blogs, competitors’, suppliers’, or distributors’ data, governmental or NGO-based analysis and papers, or from research publications. In addition, they must be able to provide their results also on mobile devices, taking into account location-based or time-based environmental data.

The lectures held at the Third European Business Intelligence Summer School (eBISS), which are presented here in an extended and refined format, cover not only established BI and BPM technologies, but extend into innovative aspects that are important in this new environment and for novel applications, e.g., pattern and process mining, business semantics, Linked Open Data, and large-scale data management and analysis.

Combining papers by leading researchers in the field, this volume equips the reader with the state-of-the-art background necessary for creating the future of BI. It also provides the reader with an excellent basis and many pointers for further research in this growing field.


Big Data Business intelligence Business process management Business semantics Indexing Linked open data OLAP Online analytical processing Ontologies Pattern mining Process mining Querying Time series analysis

Editors and affiliations

  • Esteban Zimányi
    • 1
  1. 1.Université Libre de BruxellesBrusselsBelgium

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Print ISBN 978-3-319-05460-5
  • Online ISBN 978-3-319-05461-2
  • Series Print ISSN 1865-1348
  • Series Online ISSN 1865-1356
  • Buy this book on publisher's site