About This Course

Semantic Layer & Ontology teaches you how to give raw data a shared, queryable meaning. It also teaches you which of two different tools to use for that job. You will build a real dbt semantic layer. Then you will learn what a formal ontology actually is, when it is worth the cost, and how modern tooling is closing the gap between the two.

Requirements

• Comfortable writing SQL, including joins and aggregations, with nothing more advanced required
• Comfortable working from a terminal, with Git and a Python environment installed. You will clone the lab repo and install and run dbt locally with pip
• No prior dbt, ontology, or RDF/OWL knowledge needed
• No cloud data warehouse account required. The local setup runs entirely on DuckDB

What You'll Learn

• Define entities, dimensions, and metrics in a dbt semantic layer, and query them with MetricFlow
• Understand what RDF/OWL ontologies and description-logic reasoning actually buy you, and what they cost
• Recognize when a lightweight semantic layer beats a formal ontology, and when it doesn't
• Know where graph-native approaches fit alongside both, for relationship- and path-based questions neither tool handles well

Hands-On

The course ends with a graded lab. You build a real dbt semantic layer project end to end.