Scientific Library of Tomsk State University

   E-catalog        

Image from Google Jackets
Normal view MARC view

Business Intelligence electronic resource Third European Summer School, eBISS 2013, Dagstuhl Castle, Germany, July 7-12, 2013, Tutorial Lectures / edited by Esteban Zimányi.

Contributor(s): Zimányi, Esteban [editor.] | SpringerLink (Online service)Material type: TextTextSeries: Lecture Notes in Business Information ProcessingPublication details: Cham : Springer International Publishing : Imprint: Springer, 2014Description: IX, 243 p. 95 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783319054612Subject(s): Economics | Computer Science | Data mining | Information storage and retrieval systems | Information systems | Management information systems | Economics/Management Science | Business Information Systems | Data Mining and Knowledge Discovery | Information Storage and Retrieval | Computer Appl. in Administrative Data Processing | Probability and Statistics in Computer ScienceDDC classification: 650 LOC classification: HF54.5-54.56Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
No physical items for this record

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.

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.

There are no comments on this title.

to post a comment.