Big Data Era has largely contributed in accelerating the development of large, high quality and valuable Knowledge Bases (KB) by academicians (e.g., Cyc, DBpedia, Freebase, and YAGO) and industrials (e.g., Knowledge Graph). On the other hand, serious studies have identified the crucial role of KB for analytical tasks, by offering analysts more entities (people, places, products, etc.). The availability of a huge, high quality and valuable KB may contribute on designing value-added approaches for business intelligence applications. In this paper, we first propose a novel approach for semantic DW design that considers KB in the life cycle. Secondly, based on graph formalization adapted to KB, we produce conceptual multidimensional design and a semantic ETL process that orchestrates the graph data flows from data sources to the DW storage. Finally, all steps of our approach are illustrated using the YAGO KB and deployed in Oracle RDF Semantic Graph 12c.
