Abstract
Academia has provided very performant and storage efficient technologies for fundamental Business Intelligence (BI) objects: cubes, instigated research in stream technologies resulting in renewed interest in continues and temporal queries, supplied further data mining and data exploration algorithms and research query optimizations for complex queries with variety of histograms. Database industry either incorporated into their SQL engines some of these algorithms, or tried to integrate better stand alone BI engines such as online analytical processing (OLAP), or provided their own unique solutions for BI. The innovation in BI technologies within the database offerings made business community apply relational engines to their problems. This application provided valuable feedback on performance, functionality, manageability, and integration of BI features in the Relational Database Management Systems (RDBMs). Consequently, it gave a raise to new trends in BI technologies. As a result, these new trends and issues are quickly emerging as they are being driven by the continued acceptance of the Intranet for business infrastructures.
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