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Concise and comprehensive introduction to various aspects of business intelligence (BI)
Combines traditional BI technologies with new topics such as business semantics, Big Data analysis, and Linked Open Data
Contributions conjointly written by leading researchers and industrial developers, striving for both high relevance and real-world applicability
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.
Content Level »Research
Keywords »Big Data - Business intelligence - Business process management - Business semantics - Indexing - Linked open data - OLAP - Online analytical processing - Ontologies - Pattern mining - Process mining - Querying - Time series analysis