Bryce Bartmann

Energy is arguably the most critical industry on earth, and yet the complexity of the processes and the implications of getting it wrong have been barriers to AI adoption, until now. This session will give context to the current challenges faced by the energy sector and explain how Orbital, the foundation model for energy developed by Applied Computing, can address those challenges by providing an AI model that is both physics-informed and domain specific. The session will also unpack how Databricks provides the enterprise-ready backbone for Orbital, supporting rapid data ingestion, creation, indexing, model training and more

Join us for a compelling forum exploring how energy leaders are harnessing data and AI to build a more sustainable future. As the industry navigates the complex balance between rising global energy demands and ambitious decarbonization goals, innovative companies are discovering that intelligence-driven operations are the key to success. From optimizing renewable energy integration to revolutionizing grid management, learn how energy pioneers are using AI to transform traditional operations while accelerating the path to net zero. This session reveals how Databricks is empowering energy companies to turn their sustainability aspirations into reality, proving that the future of energy is both clean and intelligent.

Real-time data is one of the most important datasets for any Data and AI Platform across any industry. Spark 4.0 and Delta 4.0 include new features that make ingestion and querying of real-time data better than ever before. Features such as: - Python custom data sources for simple ingestion of streaming and batch time series data sources using Spark - Variant types for managing variable data types and json payloads that are common in the real time domain - Delta liquid clustering for simple data clustering without the overhead or complexity of partitioning In this presentation you will learn how data teams can leverage these latest features to build industry-leading, real-time data products using Spark and Delta and includes real world examples and metrics of the improvements they make in performance and processing of data in the real time space.