Social media will spur dramatic evolutionary shifts in traditional BI architectures in several ways. For starters, vendors will bring the Wikipedia and Facebook models into the heart of their user experience, converging traditional BI with social networking, knowledge management, and collaboration architectures. Under this new “social BI” paradigm, vendors will provide information workers with tools for collecting vast pools of user-generated, subject-oriented, multimedia content, thereby supplementing and extending traditional data marts. By encouraging user-centric development of multimedia content stores, social media will accelerate the evolution of enterprise data warehouses into comprehensive “content warehouses.” By enabling applications to monitor and mine growing streams of social media content, the new generation of social BI platforms will accelerate the convergence of data mining, content analytics, and complex event processing. And this new BI platform paradigm will enable powerful social network analysis, sifting through continuing streams of transaction, behavioral, and sentiment data to identify influencers, net promoters, brand ambassadors, and other key relationships in online communities of all shapes and sizes.