It sounds like the author is calling a kind of materialized/persisted view "denormalized tables". The actual DB tables stay untouched and fully normalized.
It sure makes sense to love them, views are great. I don't know why they need a new name.
> Transformation tools such as dbt (Data Build Tool) have revolutionized the management and maintenance of denormalized tables. With dbt, we can establish clear relationships between table abstractions, create denormalized analytics datasets on top of them, and ensure data integrity and consistency with tests.
As a thought experiment. Was the original thing invented or discovered?
Many things are re-invented/rediscovered from first principles. In maths, some people prefer to think maths are created, and some prefer to think in terms of discovering/uncovering sth that was already there.
It’s complicated. Databases have entities called “views” and “materialized views” that have a specific meaning in that ecosystem. dbt let’s you define views in the abstract sense, but they’re implemented using a variety of different database primitives, like tables, temp tables, common table expressions, and views. dbt calls them “models”.
The debate over normalized/denormalized has to do with how authoritative online data should be stored. What you do with derived datasets is not really contentious; do whatever you want.
It sure makes sense to love them, views are great. I don't know why they need a new name.
> Transformation tools such as dbt (Data Build Tool) have revolutionized the management and maintenance of denormalized tables. With dbt, we can establish clear relationships between table abstractions, create denormalized analytics datasets on top of them, and ensure data integrity and consistency with tests.