Case Study: Condé Nast boosts self-service data access with dbt Cloud and Databricks Lakehouse

Condé Nast serves up multimedia content on a global scale

Condé Nast, the global media company behind digital, social, video, and print content for more than 1 billion fans, was struggling with a complex, siloed data architecture that made collaboration difficult and reduced trust in data across engineering, data science, and data warehouse teams. Working with dbt Labs and Databricks Lakehouse, the company sought a simpler, more scalable way to unify its data stack and support global growth.

dbt Labs helped Condé Nast implement dbt Cloud alongside Databricks Lakehouse on its Evergreen platform, giving teams access to shared Silver and Gold datasets and enabling reusable data models, centralized macros, and stronger lineage and testing. The results included 85 dbt models built, a 30% increase in self-service for data warehousing engineers, and 16 hours saved per data integration sprint, while also improving data trust and reducing dependency on data engineers.

Condé Nast

Nana Essuman

Senior Director of Data Engineering