Kimball in the context of the modern data warehouse: what's worth keeping, and what's not
Dimensional modeling described in the Kimball Toolbook was in its 3rd edition 15 years ago yet is still the latest in data modeling advice. So much is different in cloud warehouses that many of those best practices are now bad practices. In this video Dave Fowler, the founder of Chartio and author of Cloud Data Management goes over what no longer applies, and what does.
▶︎
Behind the Hype: Should you ever build a Data Vault in a Lakehouse?
▶︎
Introduction to dbt (data build tool) from Fishtown Analytics
▶︎
Dimensional Modeling – Declaring Dimensions
▶︎
Modern Analytics Architecture Bootcamp 2021 - Part I: Modern Cloud Data Architecture for Analytics
▶︎
Designing Your Data Warehouse from the Ground Up
▶︎
Keynote: After the AI Hype – What’s Real, and What’s Next - Richard Campbell - 2026
▶︎
Learn Data Modeling in 8 minutes: Dimensional Data Modeling, Data Vault, and One Big Table
▶︎
Dimensional Modeling
▶︎
TypeScript in Express – TypeScript Tutorial
▶︎
Dimensional Modeling to Data Vault Evolution
▶︎
The Heartbreaking Atrocity of The Ukraine War (And Why You Should Care) - James Verini
▶︎
Data Mesh, Data Fabric, Data Lakehouse - SQLBits 2022
▶︎
No Boss, No Money: The Raw Reality of China’s Gen-Z Freelancers
▶︎
Master Dimensional Modeling Lesson 01 - Why Use a Dimensional Model?
▶︎
Modern Data Warehouse explained - James Serra
▶︎
Data Modeling in the Modern Data Stack
▶︎
Functional Data Engineering - A Set of Best Practices | Lyft
▶︎
Data Engineering Principles - Build frameworks not pipelines - Gatis Seja
▶︎
Dimensional Data Model Tutorial - A Kimball Style Data Model
▶︎