Modeling for success: Building data structures that last

🌐 Global friendly sessions on September 30 & October 1

Poor data modeling is one of the most common and costly mistakes teams make when implementing dbt. Quick fixes and one-off designs may seem faster in the moment, but they create hidden risks: redundant code, fragile pipelines, and data that’s hard to trust or scale. A well-designed model is the foundation for sustainable analytics.

Join experts from dbt Labs and phData as they share proven strategies for structuring models that align to business processes, reduce complexity, and keep projects future-ready. You’ll learn why dimensional modeling is the most effective approach for dbt’s batch-oriented workflows, and how intentional design pays dividends in speed, cost, and trust.