The data modeling course that covers both the relational fundamentals and the modern patterns. ER diagrams, normalization, star schemas, NoSQL document design, and schema migration strategies — with real examples from production systems.
This is a text-first course that links out to the best supporting material on the internet instead of trying to replace it. The goal is to make this the best course on data modeling and database design you can find — even without producing a single minute of custom video.
This course is built by people who ship production data systems for a living. It reflects how things actually work on real projects — not how the documentation describes them.
Every day has working code snippets you can paste into your editor and run right now. The emphasis is on understanding what each line does, not memorizing syntax.
Instead of shooting videos that go stale in six months, Precision AI Academy links to the definitive open-source implementations, official documentation, and the best conference talks on the topic.
Each day is designed to finish in about an hour of focused reading plus hands-on work. You can do the whole course over a week of lunch breaks. No calendar commitment, no live classes, no quizzes.
Each day stands alone. Read them in order for the full picture, or jump straight to the day that answers the question you have today.
How to capture business requirements as entities, attributes, and relationships before writing a single CREATE TABLE statement. The notation that every database textbook uses and why it still matters.
1NF through 3NF with examples of what goes wrong when you skip each step. When to denormalize for performance and how to make that decision consciously.
Star schemas and snowflake schemas for analytics workloads. Fact tables, dimension tables, slowly changing dimensions, and why your warehouse query is slow.
Document modeling in MongoDB, key-value patterns in Redis, and graph modeling in Neo4j. When each beats a relational model and the failure modes of each.
Adding columns, renaming tables, and migrating data without downtime. The migration tools (Flyway, Liquibase, Alembic) and the patterns that make schema changes safe.
Instead of shooting our own videos, Precision AI Academy links to the best deep-dives already on YouTube. Watch them alongside the course. All external, all free, all from builders who ship this stuff.
End-to-end ER diagramming and normalization walkthrough. Covers the common mistakes that cause JOIN explosions in production.
Star schema design, fact and dimension tables, and slowly changing dimensions explained with real analytics use cases.
Document design patterns: embedding vs referencing, schema design anti-patterns, and the aggregation pipeline.
How production teams run schema migrations safely with Flyway, Liquibase, and Alembic.
The best way to understand any technology is to read the production-grade implementations that prove it works. These repositories implement patterns from every day of this course.
The SQL migration tool used in Day 5. Version-controlled migrations with checksums, callbacks, and rollback strategies.
The Python migration tool for SQLAlchemy projects. Auto-generates migration scripts from ORM model changes.
dbt dimensional models in practice — the best open-source reference for star schema design at scale.
The canonical NoSQL document store. Reading the schema validation source clarifies how document constraints actually work.
You know how to write code but the schema decisions haunt you. This course teaches the principles behind good database design.
You need star schemas and dimensional models that perform. This course covers Day 3 in depth with real-world examples.
You want a crisp reference for communicating modeling decisions to teams and reviewing pull requests that touch the schema.
The 2-day in-person Precision AI Academy bootcamp covers data modeling and database design hands-on. 5 U.S. cities. $1,490. 40 seats max. June–October 2026 (Thu–Fri).
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