
Most enterprise data landscapes grow organically into chaos: there is no lineage, no ownership, and no data quality – and AI cannot drink from a swamp.
In this talk, Marc Schuh explains how to build a central data lake that actually scales. Drawing on years of consulting experience, he covers the architecture, engineering practices – including data mesh, Terraform modules, and dbt tests – and, above all, the user interface (UI) that determines whether an organisation ends up with a governed data lake or a swamp.
He then explains why a central data lake is the most cost-effective path to safe, enterprise-wide AI and how AI, in turn, improves the metadata quality on which everything depends.
The session provides a concrete reference architecture, real engineering patterns, and the lessons Marc wishes he had known on day one.