Advances in Data Warehousing and Knowledge Discovery

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.