Many industries rely on demand forecasting to help them plan and make critical business decisions. TransCanada is taking steps to augment this process by leveraging AWS Machine Learning and libraries like TensorFlow to develop scalable analytics models and make data driven decisions using an existing Asset Framework structure. The latest release of the PI Integrator for Business Analytics has made this process simple by allowing users to quickly and iteratively shape and transmit historical data into AWS for consumption into an extensive list of services. Using the PI System together with AWS, TransCanada is adding business value by improving the efficiency of business processes, increasing flexibility for customers and reducing opportunities for human error to occur while planning and making business decisions.
Mitchell Browning is a Senior Developer on TransCanada's US Real Time Systems & SCADA Engineering team with a focus on Machine Learning and Analytics Platforms. Since joining TransCanada in 2016, Mitchell has provided support for the SCADA, Measurement, PI Systems, and their complimentary applications. This experience has allowed Mitchell to bring a wealth of domain-specific knowledge and technical leadership to multiple machine learning and analytics projects.
In addition to analytics development, he has a background in full-stack application development and big data management. Prior to joining TransCanada, Mitchell spent most of his career focusing on cyberinfrastructure and high-performance computing.