In this, the 10th year of Big Data LDN, in its flagship Great Dat Debate keynote panel, conference chair and leading industry analyst Mike Ferguson welcomes executives from leading software vendors to discuss key topics in data management and analytics. Panellists will debate the challenges and success factors in building an agentic enterprise, the importance of unified data and AI governance, the implications of key industry trends in data management, how best to deal with real-world customer challenges, how to build a modern data and analytics (D&A) architecture, and issues on-the-horizon that companies should be planning for today.

Attendees will learn best practices for data and analytics implementation in a modern data and AI -driven enterprise from seasoned executives and an experienced industry analyst in a packed, unscripted, candid discussion.

Sarah and Chris are both at the forefront of bringing the promise of gen AI to our actual work as data people—which is a unique challenge!  Precise truth is critical for business questions in a way that it's not for a consumer search query. Sarah Nagy is the CEO of Seek AI, a startup that aims to use natural language processing to change how professionals work with data. Chris Aberger currently leads Numbers Station AI, a startup focused on data-intensive workflow automation. In this conversation with Tristan and Julia, they dive into what this future might actually look like, and tangibly what we can expect from gen AI in the short/medium term. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.  The Analytics Engineering Podcast is sponsored by dbt Labs.