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Business Intelligence [electronic resource] : First European Summer School, eBISS 2011, Paris, France, July 3-8, 2011, Tutorial Lectures / edited by Marie-Aude Aufaure, Esteban Zimnyi.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Lecture Notes in Business Information Processing ; 96 | Lecture Notes in Business Information Processing ; 96Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012Descripción: IX, 207p. 44 illus. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9783642273582
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 650 23
Clasificación LoC:
  • HF54.5-54.56
Recursos en línea:
Contenidos:
Springer eBooksResumen: 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.
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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.

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.

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