Most enterprise data landscapes grow organically into chaos: no lineage, no ownership, no data quality and AI can't drink from a swamp.
This talk shows how to build a central data lake that actually scales. Drawing on years of consulting work this talk covers the architecture, the engineering discipline (data mesh, Terraform modules, dbt tests) and, above all, the UI that decides whether you get a governed data lake or a swamp.
This talk then shows why a central lake is the cheapest path to safe enterprise-wide AI and how AI in turn lifts the metadata quality on which everything depends.
Concrete reference architecture, real engineering patterns, and the lessons we wish we'd had on day one.
Dr. Marc Schuh is a Principal Consultant at TNG Technology Consulting in Munich. He specializes in software and enterprise architecture, where Conway’s Law frequently comes into play and reveals that many technical problems are, at their core, organizational challenges. His approach focuses on driving steady improvement through intrinsic motivation and pragmatic solutions.
Marc served as one of the tech leads in building Europe’s largest commercial data lake, migrated a legacy Visual Basic application to C# using the Strangler Pattern, and supports large enterprises in improving complex marketing data pipelines. Beyond his consulting work, he contributes to innovative prototypes — including automated performance analytics for Germany’s national canoeing team and experiments with brain–computer interfaces.
In his spare time, he maintains open-source projects promoting digital independence from major cloud providers (github.com/MarcSchuh). Before joining TNG, Marc earned a PhD in physics and competed as a 400 m wheelchair sprinter at three Paralympic Games, becoming a world champion and European record holder.
