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 concise and comprehensive introduction to business intelligence (BI) Combines traditional BI technologies with new topics like semantic databases, social network analysis, and cloud computing Contributions conjointly written by leading academic researchers and industrial developers, striving for both high relevance and real-world applicability

Autorentext
Marie-Aude Aufaure is full professor at Ecole Centrale Paris (MAS Laboratory) and head of the SAP Business Objects Chair in Business Intelligence. Her research interests deal with the analysis, retrieval and querying of unstructured data, and the combination of structured and unstructured data. Esteban Zimányi is a professor and Director of the Department of Computer and Decision Engineering (CoDE) at Université Libre de Bruxelles (ULB). His current research interests include data warehouses, spatio-temporal databases, geographic information systems, the Semantic Web and Web services.

Inhalt
Data Warehouses: Next Challenges.- Data Warehouse Performance: Selected Techniques and Data Structures.- OLAP Query Personalisation and Recommendation: An Introduction.- The GoOLAP Fact Retrieval Framework.- Business Intelligence 2.0: A General Overview.- Graph Mining and Communities Detection.- Semantic Technologies and Triplestores for Business Intelligence.- Service-Oriented Business Intelligence.- Collaborative Business Intelligence.