This page contains dbt (Data Build Tool) tutorials. dbt is a powerful open-source technology that enables teams to transform raw data into valuable insights through SQL-based workflows. Here you will find hands-on tutorials and best practices for using dbt effectively. Our dbt tutorials also serve as a resource for anyone preparing for dbt Analytics Engineering Certification Exam.
📘 Introduction In this hands-on dbt tutorial, we'll walk you through how to add and run generic data tests in dbt using YAML configuration. These built-in tests help ensure your data quality and integrity, without writing any custom SQL. 📌 This is a must-know topic for the dbt Analytics Engineering...
📘 Introduction In this hands-on dbt tutorial, we'll walk you through how to use Common Table Expressions (CTEs) effectively in dbt models - an essential concept for modular, readable, and testable SQL. 📌 This is a must-know topic for the dbt Analytics Engineering Certification Exam, so mastering it now puts...
📘Introduction In this hands-on dbt tutorial, we'll walk you through how to describe and document your data models using schema.yml in dbt. 📌 This is a must-know topic for the dbt Analytics Engineering Certification Exam, so mastering it now puts you one step closer to passing the exam...
📘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...
📘 Introduction The dbt Analytics Engineering Certification Exam can be challenging—but with the right preparation strategy, you can pass with confidence. This guide brings together the best official resources and practical tutorials to help you stay focused, study smarter, and succeed. 📋1️⃣ Read the official dbt Study Guide Begin with...
📘 Introduction dbt gives you the power to transform raw data into clean, trusted models. But writing SQL is just the starting point. To truly get value from dbt, you need practices that keep your code organized, your models reliable, and your team moving fast. Whether you're a beginner...
📘Introduction Once you've created models in dbt, you can reference them using the ref() function. This is fundamental to how dbt builds dependencies and orchestrates model execution. In this hands-on tutorial, we’ll show you how to use the ref()function within a sample project. 📌 This is a...
📘Introduction In this step-by-step tutorial, we’ll walk you through how to install and use packages in dbt to supercharge your data transformations with reusable macros, models, and integrations. 📌 This is a must-know topic for the dbt Analytics Engineering Certification Exam, so mastering it now puts you one step closer...
📘Introduction If you're new to dbt (data build tool) and want to transform raw data into clean, analytics-ready tables using Python, you're in the right place. In this step-by-step tutorial, we’ll walk you through how to build your first Python model in dbt, step by...