Applying DRY Principles in dbt: Tips and Best Practices

📘Introduction

In Software Engineering, DRY stands for Don't Repeat Yourself — a fundamental principle aimed at reducing repetition, improving maintainability, and increasing code clarity. In the world of data transformation with dbt (data build tool), applying DRY principles helps ensure that your SQL code is modular, reusable, and easy to manage as your project scales.

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💡What are DRY Principles?

The DRY principle encourages you to avoid duplicating logic and instead abstract reusable pieces. In dbt, this means leveraging the features that allow you to modularize your SQL code and make your transformations clean and consistent.

🔀1️⃣ Modularize with CTEs

Rather than writing long, complex SQL queries in a single block, break your logic into Common Table Expressions (CTEs). This approach improves readability, simplifies debugging, and makes your code easier to test and maintain.
Plus, CTEs let you create a series of step-by-step transformations — much like a data pipeline — where each step builds on the previous one to gradually shape your data.