Masroor Khan, Public Service Enterprise Group (PSEG)
Ann Moore, AVEVA
Paul Bower, Southwire
![Joyce LePage](http://assets.swoogo.com/uploads/thumb/2288669-63bc50203a5e8.jpg)
![Masroor Khan](http://assets.swoogo.com/uploads/thumb/3889450-6635314e5fe78.jpg)
![Ann Moore](http://assets.swoogo.com/uploads/thumb/2683066-648b55fe23168.jpg)
![Paul Bower](http://assets.swoogo.com/uploads/thumb/3889463-663531de16aac.jpg)
To make informed decisions across various business units, it is imperative that data coming from a utility’s thousands of assets be readily accessible and presented in a clear, actionable manner. In this session, attendees will hear two separate presentations providing examples and strategies that helped utilities get the most from their data analytics programs and processes. The first presenter will discuss a strategic fusion of disparate data, spatial intelligence, and artificial intelligence to prioritize cost-effective remedies for enhancing grid reliability. Attendees will learn how combining these technologies allows utilities to prioritize asset improvements, equipment modernization, network optimization, and vegetation management. The presenter will explain how this approach enables utilities to navigate the complex grid improvement landscape with informed decision-making capabilities that benefit both the utility and consumers. The second presenter will reveal how a utility used IIoT sensors, distributed energy resources (DER) and behind-the-meter (BTM) data to exponentially grow data volume, velocity and variety, providing users with the right tools to perform ad-hoc analyses within the same environment. This capability also allows users to gain valuable insights on how various factors (either time-based or business processes-based) affect grid performance. The speakers also will explore available technologies and innovations, such as geospatial analytics, predictive/prescriptive analytics, AI, generative AI, machine learning, and cloud computing, as well as provide examples illustrating IT/OT convergence.