Data stream warehousing combines the real-time data loading of data stream management systems and the long histories and deep analytics of data warehouses. AT&T generates many diverse high-volume data streams as part of its normal operations. To make full use of this flood of data, we have been developing technologies for data stream warehousing, allowing analysts to develop applications such as data mining, alerting, and troubleshooting tools across multiple data sources, for example in the Darkstar data warehouse. Data stream warehousing exposes some unique data management problems. In this talk, I introduce data steam warehousing, the challenges that real-world data feeds present, and a collection of technologies for handling these problems.