Webinar | Your Water Utility's Data Journey: Where to Start

E Source Webinar | Your Water Utility's Data Journey: Where to Start

Water utilities are generating more data every year, but overcommitted teams, outdated legacy systems, and competing priorities can make it difficult to turn that information into timely, trusted insight. 

This session cuts through the complexity with a brief, practical look at how water utilities, regardless of size or current maturity, can identify realistic first steps for getting more value from the data they already possess. 

Attendees will learn a framework for defining what they want their data to tell them, evaluating whether their systems are capturing the information they need, and getting scattered data into shape that supports reporting, operational decisions, analytics, and future AI applications.

Key takeaways

• Learn what your data is actually worth. Find out how understanding where your data comes from, what it means, and how it's used turns information you already collect into insight.
• Spot the gaps between your systems. SCADA, AMI, LIMS, work order, and GIS each hold a piece of the story. See how to uncover competing sources of truth and integration gaps that are quietly limiting your insight.
• Get AI-ready without a massive overhaul. Explore practical paths, from basic data consolidation to a governed lakehouse to data fabric, that put trustworthy data into your reporting, analytics, and AI.
   

Presenter: Norv Clontz
Norv is the Vice President of AI Strategy & Impact where he is responsible for leading advanced data and analytics initiatives as well as developing service offerings.

He has led consulting engagements for Fortune 500 clients around the world in industries including utilities, oil & gas, automotive, retail, and financial services.  Norv led the business analytics practice at a management and IT consulting firm before joining Duke Energy as its first data scientist in 2015. Progressing from individual contributor to people leader, he built a record of creating high-performance data science teams within the utility. He also established and lead AES US Utilities’ data science and analytics business unit.