Data warehousing
and
knowledge discovery
is an extremely active research area
where a number of methodologies and paradigms converge, with coverage of
both theoretical issues and practical solutions. The area of data warehousing
and knowledge discovery has been widely accepted as a key technology for en-
terprises and organizations, as it allows them to improve their abilities in data
analysis, decision support, and the automatic extraction of knowledge from data.
With the exponentially growing amount of information to be included in the
decision-making process, the data to be considered are becoming more and more
complex in both structure and semantics
. As a consequence, novel developments,
both at the methodological level, e.g.,
complex analytics ov
er data, and at the
infrastructural level, e.g., cloud comput
ing architectures, a
re necessary. Orthog-
onal to the latter aspects, the knowledge discovery and retrieval process from
huge amounts of heterogeneous complex data represents a significant challenge
for this research area.
