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Business Intelligence

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

  • Marie-Aude Aufaure
  • Esteban Zimányi

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

Table of contents

About this book

Introduction

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.

Keywords

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

  • DOI https://doi.org/10.1007/978-3-642-36318-4
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-36317-7
  • Online ISBN 978-3-642-36318-4
  • Series Print ISSN 1865-1348
  • Series Online ISSN 1865-1356
  • Buy this book on publisher's site