Constellation operates the largest nuclear fleet in the United States. For them, one of the hardest parts of preparing for AI wasn’t choosing models, it was agreeing on what the data means. Constellation’s team is building a governed Enterprise Data Platform (EDP) on Databricks to make data consistent and usable across the business, and its approach offers a practical roadmap for other enterprises.

Constellation is the nation's largest producer of clean and reliable energy, with generating capacity equivalent to the needs of 27 million homes and approximately 2.5 million retail customer accounts. That breadth of operations and customer relationships is why shared definitions and governance matter to their data work.

Constellation collects data from asset management, supply chain, commercial and trading systems, and operations across the fleet. These are feeding everything from near-real-time market models to nuclear telemetry. In a business where safety and reliability come first, getting definitions and governance right matters. That risk profile drives every architectural choice that follows.

The problem: High-quality data, no shared semantics

Teams across Constellation built strong data capabilities for their own work. However, questions that spanned those teams still required additional effort to connect information and reconcile differences in how it is defined. Data sat in dozens of places, with no shared semantic layer defining what it meant across domains.