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 Second 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., machine learning,
logic networks, graph mining, business semantics, large-scale data
management and analysis, and multicriteria and collaborative
decision making.
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.
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