We’re back for a relaxed, practical evening on time series- the stuff we use every day for demand, reliability, and asset health. No hype; just what works and what doesn’t. We will have [Matthew Parker](https://www.linkedin.com/in/matthew-j-parker/) from Endeavour Energy who will cover **Success Creates Problems: Lessons from Scaling Databricks from Time Series Data to an Enterprise AI Platform** What started as a migration of operational time-series data into Databricks quickly evolved into something much bigger. In this session, we'll share our journey from a single use case to an enterprise platform supporting analytics, planning, AI, applications and governance. We'll discuss the challenges we faced around ingestion costs, platform adoption, access management and data governance, and how we're now establishing the foundations needed to scale Databricks sustainably across the business. You will gain practical insights into the realities of enterprise Databricks adoption, including lessons learned, unexpected outcomes and the opportunities ahead with AI, applications and Lakebase. To add to the first talk, we will also have [Allan Leung](https://www.linkedin.com/in/allan-leung/) from Databricks who will show how you can build and run time‑series pipelines on the Lakehouse - the patterns that stick, the ones to avoid, and a few “wish I knew this earlier” tips. Think of it as an **Art of the possible tour for taming time‑series data**. We’ll have light snacks and drinks to keep the conversations going. Come meet your industry peers, learn something new, and share what you’re working on! Looking forward to seeing you there!
