PG&E will share a practical framework for capturing and managing historical data that improves reporting, analytics, and decision-making across utility operations. Rather than relying on snapshot-based approaches, the solution uses Slowly Changing Dimension (SCD) Type 2 modeling to preserve meaningful changes over time while creating a structured, query-friendly history of operational data.

Using a real-world implementation, attendees will learn how this approach improved data reliability, simplified reporting, and enabled accurate point-in-time analysis for operations, compliance, and financial reporting. The session will also demonstrate how scalable historical data models reduce pipeline complexity while making analytics more accessible for analysts and business users.

Session Takeaways:
•        How to build scalable historical data models using SCD Type 2 principles 
•        Practical approaches for supporting reliable point-in-time reporting and trend analysis 
•        Best practices for simplifying data pipelines while improving data quality and accessibility 
•        Techniques for efficiently querying historical data for dashboards and reporting 
•        Lessons learned implementing scalable historical data frameworks in a utility environment