patterns

Discover how styling transforms your dbt workflow—from smart naming and clean SQL formatting to dynamic Jinja, YAML clarity, and enforced standards with SQLFluff and dbt‑checkpoint. This guide turns pipelines into readable, maintainable stories that boost onboarding and trust.

Learn how to seamlessly run your dbt Core project with Apache Airflow. We cover the different methods to setup, code repo, video tutorial for local dev, and best practices to help you orchestrate dbt runs using Airflow: the easiest way to modernize your data workflows.

Learn how to standardise logging in dbt macros for clear, consistent CLI output. This guide shows you how to create a reusable logging macro, making debugging and tracking macro activity in your dbt projects easier and more efficient.

Automate PII tagging in your dbt project using OpenAI! Streamline data governance, ensure compliance, and save time by leveraging AI to detect and flag sensitive information in your data models. Integrate this workflow into CI/CD for robust, scalable data protection.

If people don’t trust the work of the analytics engineering team, then all the effort you put in doesn’t matter. One of the best ways is by using test-driven development (TDD).

Explore the pros and cons of dbt monorepo vs multi-repo setups. Learn when to use each for scalable, collaborative analytics engineering workflows.