Busting Data Modeling Myths: Truths and Best Practices for Data Modeling in the Lakehouse

Unlock the truth behind data modeling in Databricks. This session will tackle the top 10 myths surrounding relational and dimensional data modeling. Attendees will gain a clear understanding of what Databricks Lakehouse truly supports today, including how to leverage primary and foreign keys, identity columns for surrogate keys, column-level data quality constraints and much more. This session will talk through the lens of medallion architecture, explaining how to implement data models across bronze, silver, and gold tables. Whether you’re migrating from a legacy warehouse or building new analytics solutions, you’ll leave equipped to fully leverage Databricks’ capabilities, and design scalable, high-performance data models for enterprise analytics.