Data warehousing and Business Intelligence (BI) are the mainstays of traditional information architecture and integration. However, innovative and disruptive data technologies, increasing data volumes and sources of data, more complex data integration and quality issues, and the need for lower data latencies are forcing data architects to change how they approach tomorrow’s information architecture. While these latter developments do shake up the status quo, they do not mean the traditional data warehouse (DW) is no longer needed. Instead, data architects must extend the current DW architecture beyond its established "walls" to embrace new data management approaches in a consistent and seamless manner.