The data and AI space moves fast. If you don’t stop and look around once in a while, you just might miss it,” said Ferris Bueller if he was in tech, probably. No one knows this more than Tomasz Tunguz, General Partner at Theory Ventures and investor in Looker, Motherduck, Monte Carlo, Hex, and other pioneering data companies. In this talk, Tomasz will walk through the top 10 trends he sees defining data and AI in 2025, including the rise of ML engineers, the evolution of the LLM production stack (vector databases, anyone?), the role of data observability in generative AI deployment, and the explosion of query engines, among other critical technologies.

Measuring data quality across different business domains isn't always straightforward—especially when AI adoption adds layers of complexity. Are you confident your data quality initiatives are delivering real business value?

Don’t miss this chance to learn how to transform your data quality processes and ensure your data is ready for AI-driven success.

Your AI models are only as good as the data behind them. When poor data sneaks in, predictions falter, trust crumbles, and performance takes a nosedive.

But here’s the good news: you can spot and resolve data quality issues before they wreck your AI projects. In our upcoming session, we’ll show you how to:

• Integrate automated data observability and collaborative exploration tools
• Quickly pinpoint anomalies and root causes across your AI pipeline
• Keep stakeholders informed and maintain trust in your data

Walk away with proven tactics to safeguard your models, scale AI smoothly, and ensure your data works for you—not against you.