About This Course

Semantic Layer & Ontology teaches you how to give data a shared meaning that people and AI agents can use. You learn two tools for this job. A semantic layer defines business metrics one time and serves them to every tool. An ontology describes the things in a domain and how they relate. You build both, and you connect an agent to each one.

Requirements

• You can write SQL with joins and aggregations.
• You can use a terminal, Git, and Python. You install dbt, MetricFlow, and RDF libraries locally with uv.
• You do not need prior knowledge of dbt, RDF, OWL, SHACL, Brick, or ASHRAE 223.
• You do not need a cloud data warehouse. The hands-on work runs on DuckDB and in Python on your computer.
• For the agent units, you need access to Claude. The course explains how to request it.

What You Will Learn

In the first half, you learn why semantic layers exist and how dbt and MetricFlow define entities, dimensions, and metrics. You compare dbt with Snowflake Semantic Views, Databricks Metric Views, Cube, and the Apache Ossie interchange standard. You learn how to design grain, metadata, tests, and access. Then you build a complete semantic layer for a fictional SaaS company in a step-by-step tutorial. You add every metric type, saved queries, and exports. You put a Claude agent on top of it and evaluate the agent against a text-to-SQL baseline.

In the second half, you learn what an ontology is and how to build one. You write RDF and Turtle, query with SPARQL, reason with OWL in Protégé and in Python, and validate data with SHACL. You model buildings with Brick and ASHRAE 223, and you learn how to combine them with RealEstateCore. Then you connect agents to ontologies. You build Claude tools over a Brick model, and you build a loop that lets Claude map building point labels to Brick classes while SHACL checks every result.

How the Course Is Structured

The course has six sections. Section 1 covers semantic layer foundations. Section 2 is the hands-on semantic layer tutorial. Section 3 covers ontology foundations. Section 4 covers Brick and ASHRAE 223. Section 5 covers agents on semantic layers and ontologies. Section 6 covers when to choose an ontology, the graded lab, and course feedback. Most subsections start with a free external course or official documentation. Original deep dives then go further. Each section ends with a graded Section Check.

Hands-On

The course ends with a graded lab. You build a dbt semantic layer project end to end. The ontology exercises inside Sections 3, 4, and 5 are not graded.