The Center for Building Performance and Diagnostics at Carnegie Mellon University has been using the PI System for data collection, aggregation and analytics for years. In recent work, researchers were able to predict (forecast) energy consumption across buildings, detect faults, take actions to mitigate issues in real-time and deliver cost savings, using real time data collected by the PI System, with a cloud based Machine learning solution (Microsoft Azure ML).