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Why does style matter?​ Style might seem like a trivial, surface-level issue, but it's a deeply material aspect of a well-built project. A consistent, clear style enhances readability and makes your project easier to understand and maintain. Highly readable code helps build clear mental models making it easier to debug and extend your project. It's not just a favor to yourself, though; equally imp

Dimensional modeling is one of many data modeling techniques that are used by data practitioners to organize and present data for analytics. Other data modeling techniques include Data Vault (DV), Third Normal Form (3NF), and One Big Table (OBT) to name a few. While the relevance of dimensional modeling has been debated by data practitioners, it is still one of the most widely adopted data modelin

We use the terms "nodes" and "resources" interchangeably. These encompass all the models, tests, sources, seeds, snapshots, exposures, and analyses in your project. They are the objects that make up dbt's DAG (directed acyclic graph). The --select and --selector arguments are similar in that they both allow you to select resources. To understand the difference, see Differences between --select and

Why does structure matter?​ Analytics engineering, at its core, is about helping groups of human beings collaborate on better decisions at scale. We have limited bandwidth for making decisions. We also, as a cooperative social species, rely on systems and patterns to optimize collaboration with others. This combination of traits means that for collaborative projects it's crucial to establish consi

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