Roberto Robles Nacif

Building an app has never been easier. Deploying an enterprise app— governed, scalable, connected to real-time data— has never been harder. Store associates, restaurant managers, and operations teams make thousands of decisions a day— but the apps they rely on are slow to build, disconnected from analytics, and starved of real-time context. The reason? A wall between analytical and operational systems that forces teams to maintain fragile ETL pipelines, over-provision databases, and wait months for production-ready tools. Lakebase tears that wall down. Databricks' serverless Postgres eliminates the infrastructure overhead, the ETL pipelines, and the DBA bottleneck that have kept intelligent apps out of frontline hands. In this session, we'll show what it means to build AI-first applications for consumer industries, walking through the end-to-end process: from use case design to live deployment, including a live app build on stage. Hear from brands already shipping Lakebase-powered apps, and leave with a repeatable framework for turning lakehouse intelligence into the tools your frontline teams actually use.

Supply chain volatility is the new normal, and the old playbook of siloed forecasting, batch EDI, and reactive logistics can't keep up. The next frontier of CPG-retail performance isn't just efficiency; it's collaboration. Leading companies are replacing linear supply chains with intelligent networks that sense and respond in real time, unifying retailer POS, demand signals, and inventory data to power AI models that continuously optimize forecasting, replenishment, and risk detection. And they're doing it on a single, governed platform where shared data fuels not just dashboards and insights, but AI agents that act autonomously— triggering replenishment, reallocating inventory, and adjusting plans the moment conditions change. In this session, hear directly from the retailers and CPGs making this shift. Learn how open data sharing, AI-powered demand sensing, and joint planning on Databricks are turning adversarial transactions into growth partnerships, and why the companies that collaborate on data today will own the shelf tomorrow.

As first-party data becomes increasingly invaluable to organizations, Walmart Data Ventures is dedicated to bringing to life new applications of Walmart’s first-party data to better serve its customers. Through Scintilla, its integrated insights ecosystem, Walmart Data Ventures continues to expand its offerings to deliver insights and analytics that drive collaboration between our merchants, suppliers, and operators.​Scintilla users can now access Walmart data using Cloud Feeds, based on Databricks Delta Sharing technologies. In the past, Walmart used API-based data sharing models, which required users to possess certain skills and technical attributes that weren’t always available. Now, with Cloud Feeds, Scintilla users can more easily access data without a dedicated technical team behind the scenes making it happen. Attendees will gain valuable insights into how Walmart has built its robust data sharing architecture and strategies to design scalable and collaborative data sharing architectures in their own organizations.