© 2013

Business Intelligence

Second European Summer School, eBISS 2012, Brussels, Belgium, July 15-21, 2012, Tutorial Lectures

  • Marie-Aude Aufaure
  • Esteban Zimányi


  • Concise and comprehensive introduction to business intelligence (BI)

  • Combines traditional BI technologies with new topics such as business semantics, Big Data analysis, and multicriteria decision making

  • Includes recent developments in underlying basic technologies such as machine learning, logic networks, and graph mining

  • Contributions conjointly written by leading academic researchers and industrial developers, striving for both high relevance and real-world applicability

Textbook eBISS 2012

Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 138)

Table of contents

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 Second 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., machine learning, logic networks, graph mining, business semantics, large-scale data management and analysis, and multicriteria and collaborative decision making.

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.


BPEL BPMN Bayesian Networks Big Data Business Intelligence Business Process Management Business Semantics Data Warehouses Graph Mining Machine Learning MapReduce Markov Logic Networks Multicriteria Decision Making OLAP Online Analytical Processing Ontologies

Editors and affiliations

  • Marie-Aude Aufaure
    • 1
  • Esteban Zimányi
    • 2
  1. 1.MAS LaboratoryEcole Centrale ParisChâtenay-MalabryFrance
  2. 2.Department of Computer and Decision Engineering (CoDE)Université Libre de BruxellesBrusselsBelgium

Bibliographic information

Industry Sectors
Chemical Manufacturing
IT & Software
Consumer Packaged Goods
Finance, Business & Banking