Data Interoperability with Unity Catalog

This course walks practitioners through the full spectrum of data modelling approaches on the Databricks Data Intelligence Platform - from classical data warehouse techniques (Inmon, Kimball, Data Vault 2.0), through Feature Store-driven ML use cases, to productising data via Data Products on Unity Catalog.

Each modelling approach is introduced with a lecture, then reinforced with a hands-on demo against a shared dataset (TPC-H samples). The course finishes with a comprehensive end-to-end lab that exercises ERM, dimensional modelling, Data Vault 2.0, and the Feature Store in a single integrated workflow.

Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.

Languages Available: English | 日本語 | Português BR | 한국어

In this course, you will explore core SQL programming and procedural logic skills within Databricks, focusing on how to build modular, maintainable, and production-ready analytics workflows. You’ll start by learning about key SQL constructs—such as Common Table Expressions (including advanced recursive CTEs), session-scoped objects like temporary views and tables, and User Defined Functions—that make your SQL development cleaner and more reusable. The course then guides you through advanced SQL scripting techniques using compound statements, variables, control flow, conditionals, loops, and robust error handling to create structured and flexible SQL processes. You will also learn how to guarantee data consistency across these multi-step pipelines using ACID-compliant multi-statement transactions. Finally, you’ll discover how to encapsulate logic into SQL Stored Procedures and orchestrate complex workflows with Lakeflow Jobs and migration strategies, transforming legacy tasks into modular, automated pipelines that leverage the full capabilities of the Databricks platform.

In this course, you’ll learn how to empower your data consumers to get validated business insights with less burden on you and the rest of your enterprise's data and AI team. Through building a semantic layer on top of your gold layer, you'll offer decision makers and business analysts the opportunity to explore key business performance indicators in novel ways, while still maintaining efficient data operations and enterprise-vetted metrics.