Prerequisite: None
Jason Doerr
Enterprise Data Governance Manager
Xcel Energy
Xcel Energy, an electricity and natural gas delivery company, is on a journey to modernize their analytics capabilities to drive key use cases around wildfire mitigation and energy demand forecasting. Ultimately, the goal is to create a comprehensive self-service marketplace for consuming data products. Xcel worked with partners to create a unified data platform that will support their data and analytics needs.
A key challenge for Xcel was to ensure adequate and proper governance for all the data coming into their analytics environment. Key data sources must provide high-quality data to drive machine learning models and analytics for fire prevention indexes and wildfire mitigation use cases. These include customer warning systems for potential power shutdowns and workforce dispatching to prioritize vegetation management efforts.
In this session, attendees will learn:
- How Xcel Energy is integrating disparate data sources that include weather, asset, customer, and workforce information to calculate fire prevention indexes for specific geographical areas and power machine learning models that prioritize key decisions designed to mitigate and reduce wildfire risk
- How Xcel is working to govern multiple data sets to ensure that only high-quality, cataloged data is used to drive critical metric calculations and train vital machine learning models
- How to manage and overcome challenges associated with acquiring data from multiple sources
- How analytics and machine learning can drive successful outcomes for very complicated and sophisticated use cases