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 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...
📘Introduction If you're new to dbt (data build tool) and want to transform raw data into clean, analytics-ready tables — you're in the right place. In this step-by-step tutorial, we’ll walk you through how to build your first SQL model in dbt, step by step. 📌 This...
Introduction In the age of data-driven decision making, having a powerful data architecture is crucial. The Medallion Architecture is a proven data architecture pattern that helps in organizing data across different layers of refinement. When combined with dbt (data build tool), it becomes a powerful and scalable way to manage...
Introduction Keeping the data fresh in your data warehouse is crucial. In dbt (data build tool), source freshness checks help ensure that the data coming from your sources is up-to-date and trustworthy, enabling teams to confidently build reliable models downstream. This is where defining source freshness in the sources.yml...
Introduction Once you've defined sources in dbt, you can reference them using the source() function. This is essential for dbt to identify dependencies between sources and models. In this hands-on tutorial, we’ll show you how to use the source() function with a sample project. 📌 This is a...
Introduction In dbt (data build tool), sources represent raw data tables that already exist in your data warehouse - often provided by upstream systems like operational databases, APIs or other applications. Defining these sources in sources.yml is a crucial step in your data project. This tutorial will guide you...
Introduction Seeds in dbt are a simple and powerful way to load static data - such as reference tables, lookup data, or mapping tables - directly into your data warehouse. In this tutorial, you'll learn what seeds are and how to use them effectively. Since this topic is...
Introduction Want to start with dbt core but don’t know where to begin? Don’t worry! In this tutorial, we'll walk through setting up a new dbt project from scratch - we cover the entire process from creating a virtual environment to initializing your project and verifying...
Introduction Modern data work doesn’t always require complex infrastructure. If you're looking for a fast, local-first analytics stack, dbt + DuckDB is a powerful combination. In this tutorial, we'll walk through connecting dbt to DuckDB — perfect for analysts, developers, and data enthusiasts who want simplicity without...