Chad Novek

Forecasting sales at more than 7,000 retail stores generates frequent inquiries into forecast drivers, and traditional methods like driver dashboards or SHAP fail to give field leaders clear narratives. Data scientists were spending days writing ad‑hoc SQL to answer basic “why” questions. In partnership with Databricks, we built an AI/BI Genie-powered Research Agent that delivers fast, plain‑language forecast explanations using governed data. The agent joins core datasets, computes variances and accuracy metrics, correlates key drivers and links every answer to underlying SQL, cutting analysis time from days to minutes and revealing model biases. This session covers how we used Unity Catalog as the semantic backbone and encoded business rules in the Genie Knowledge Store so the agent reasons like a retail analyst. We’ll demo the agent with Deep Research and share key lessons and a repeatable blueprint for operationalizing Genie.

Conversational analytics promises to democratize data, but the path from promise to production looks different in every organization. In this session, cross-industry leaders pull back the curtain on their Genie deployments spanning four distinct functional domains: global supply chain, commercial sales and marketing, workforce staffing optimization, and healthcare intelligence for reducing readmissions. You'll hear what drove adoption, where implementation got messy, and how each team defined, and measured, value. Whether you're evaluating conversational AI for the first time or scaling an existing deployment, this cross-industry conversation delivers the unfiltered perspective you won't find in a case study.