Building the foundation for agentic data engineering

AI is changing what data engineering teams can deliver. But realizing that potential requires operational context that tells AI what data means, where it comes from, how it flows, and what breaks. Orchestration is where that context lives.

With an orchestration foundation in place, AI stops being a productivity tool for individual engineers and starts becoming a force multiplier for your entire data organization: accelerating how new data products get built, reducing the operational burden that keeps teams in reactive mode, and giving leaders visibility into what's running and what's at risk.

In this webinar, we will walk through what it takes to build that foundation, and how Otto, our data engineering agent, puts it into practice with real customer examples.

You'll learn:

• Why orchestration context, not semantic layers or documentation, is what separates AI that helps from AI that can be trusted
• What a true data engineering agent looks like in practice, and how teams are using one today
• How to give your data team more leverage without adding headcount