The issue of supporting warehousing and analytics over big Web data is more and more important at now. This emerging trend is stirred-up by recent advances of big data technologies that are pervading challenging Web application scenarios such as Web recommendation systems, Web advertisement systems, Deep Web, Wisdom Web, Social Web and, not last for relevance, social networks. In each of these application scenarios, big Web data play a critical role in order to support decision-making processes that can become relevant for a wide family of society sectors, ranging from social scenarios to e-government scenarios, from e-procurement scenarios to smart city scenarios, and so forth. To this end, big Web data must be collected, cleaned, stored, periodically-integrated with recent updates, aggregated and queried as to fully-support truly big data analytics processes over them. These strict requirements depict a complex setting where a plethora of research problems arise.
