Esteban Zimányi

Marie-Aude Aufaure

Business Intelligence (BI) promises an organization the capability of collecting and analyzing internal and external data to generate knowledge and value, providing decision support at the strategic, tactical, and operational levels. Business Intelligence is now impacted by the Big Data phenomena and the evolution of society and users, and needs to take into account high-level semantics, reasoning about unstructured and structured data, and to provide a simplified access and better understanding of diverse BI tools accessible trough mobile devices. 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. The lectures held at the First European Business Intelligence Summer School (eBISS), which are presented here in an extended and refined format, cover not only established BI technologies like data warehouses, OLAP query processing, or performance issues, but extend into new aspects that are important in this new environment and for novel applications, e.g., semantic technologies, social network analysis and graphs, services, large-scale management, or collaborative decision making. Combining papers by leading researchers in the field, this volume will equip the reader with the state-of-the-art background necessary for inventing the future of BI. It will also provide the reader with an excellent basis and many pointers for further research in this growing field.

First European Summer School, eBISS 2011, Paris, France, July 3-8, 2011, Tutorial Lectures

Business Intelligence

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.

Marie-Aude Aufaure

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