Business Intelligence Third European Summer School, eBISS 2013, Dagstuhl Castle, Germany, July 7-12, 2013, Tutorial Lectures /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Zimányi, Esteban (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2014.
• Σειρά: Lecture Notes in Business Information Processing, 172
• Θέματα: Business.; Information technology.; Business > Data processing.; Mathematical statistics.; Data mining.; Information storage and retrieval.; Application software.; Business and Management.; IT in Business.; Data Mining and Knowledge Discovery.; Information Storage and Retrieval.; Computer Appl. in Administrative Data Processing.; Probability and Statistics in Computer Science.

 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 Third 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., pattern and process mining, business semantics, Linked Open Data, and large-scale data management and analysis. 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. 

 Introduction to Pattern Mining -- Process Mining in the Large: A Tutorial -- Ontology-Driven Business Intelligence for Comparative Data Analysis -- Open Access Semantic Aware Business Intelligence -- Transparent Forecasting Strategies in Database Management Systems -- On Index Structures for Star Query Processing in Data Warehouses -- Intelligent Wizard for Human Language Interaction in Business Intelligence.