AI Inference for Mission-Critical Applications | Run AI Where Your Data Lives

What happens when your AI system stops responding in the middle of a critical decision? This demo shows how organizations run AI inference for real-world applications like pneumonia detection to: See how Cloudera AI Inference Service enables teams deploy and monitor multiple models with full control, predictable costs, and no dependency on external APIs, so mission-critical AI keeps working when it matters most.

Why Enterprise Data Strategy Must Start with Business Strategy

Learn what happens when the executive accountable for data strategy is also the executive accountable for the business results that depend on it. Saugata Saha, President of S&P Global Market Intelligence and Chief Enterprise Data Officer at S&P Global, shares how he manages one of the world's largest financial data estates while driving business outcomes across public and private markets. He breaks down the four pillars of S&P Global's data strategy, the federated organizational model that connects data teams to business value, and why capturing ROI from AI requires deliberate workflow transformation.

Ep 73 | Out of This World AI: Inside Spaceflight with Jeanette Epps

Human spaceflight is one of the few domains in which data and human judgment must work together flawlessly under extreme pressure. That makes it a powerful lens for understanding what it takes to build resilient, intelligent systems here on Earth. In this Women Leaders in Technology spotlight episode of The AI Forecast, Paul Muller sits down with former NASA astronaut Dr. Jeanette Epps to explore what complex, high-stakes environments can teach us about AI.

How to Sync Semantic Models Between ThoughtSpot and Snowflake with Cortex Code

Migrating semantic models between ThoughtSpot and Snowflake just got significantly faster. Our Senior Product Manager, Damian Waldron, walks through how to use ThoughtSpot's Agent Skills in Snowflake Cortex Code (CoCo) to migrate and sync between ThoughtSpot Models and Snowflake Semantic Views, including complex schemas with fan traps, semi-additive measures, and shared dimensions. In this video you’ll learn how to.

How to Prevent AI Hallucinations: 3 Hidden Threats When AI Analyzes Your Data

A VP of Marketing presents an AI-generated performance review on a Monday morning. The CAC numbers are clean. The trend lines are directional. The exec summary recommends a $200K budget reallocation from paid search to organic content. The CFO nods. The budget shift is approved before lunch. Two weeks later, an analyst spot-checks one figure against the source system. The number doesn’t exist anywhere in the connected data.

Omni-channel AI: The next frontier for Data and Analytics

What marketing mastered years ago, product teams are only now beginning to understand. For decades, marketing has operated on a simple but powerful principle: don't make your customers come to you, go to them. Meet them on the channels they already use, speak in the language they already speak, and show up where they already spend their time. The result was omni-channel marketing, a discipline that transformed how brands engage with the world.