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In this session, we explore how organizations can take control of their AI industrialization journey by building scalable, trusted, and governed data workflows. The talk highlights the most pressing challenges faced by data teams as they move from isolated machine learning (ML) experiments to enterprise-wide AI adoption. Drawing on insights from Dataiku’s platform leadership, viewers will learn how to balance speed with control, extend AI capabilities to broader teams, and ensure models are not only performant but also cost-effective and compliant. Through real-world examples—including major global banks and insurers—you’ll see how companies are using modern platforms like Dataiku alongside Starburst to streamline deployment, foster collaboration, and eliminate the bottlenecks of legacy infrastructure. The conversation focuses on maintaining visibility and trust across the entire project lifecycle while delivering business value at scale. This session is essential viewing for data professionals looking to operationalize AI in a secure, efficient, and future-proof way. #AIatScale #DataEngineering #MLops #DataDemocratization #EnterpriseAI #GovernedAI #StarburstData #Dataiku #DataNova #AIInfrastructure #AITrust #DataStrategy #AIPlatform