The vision of an interconnected and open Web of data is, still, a chimera far from being accomplished. Fortunately, though, one can find several evidences in this direction and despite the technical challenges behind such approach recent advances have shown its feasibility. Semantic-aware formalisms (such as RDF and ontology languages) have been successfully put in practice in approaches such as Linked Data, whereas movements like Open Data have stressed the need of a new open access paradigm to guarantee free access to Web data. In front of such promising scenario, traditional business intelligence (BI) techniques and methods have been shown not to be appropriate. BI was born to support decision making within the organizations and the data warehouse, the most popular IT construct to support BI, has been typically nurtured with data either owned or accessible within the organization. With the new linked open data paradigm BI systems must meet new requirements such as providing on-demand analysis tasks over any relevant (either internal or external) data source in right-time. In this paper we discuss the technical challenges behind such requirements, which we refer to as exploratory BI, and envision a new kind of BI system to support this scenario.