📘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 to passing the exam and leveling up your data engineering skills! 👨‍🎓

✅ Prerequisites

Before you start, make sure you have:

☑️ A dbt project set up

📦 What are dbt packages?

dbt packages are reusable collections of dbt models, macros, seeds, and tests that can be shared and versioned across multiple projects. They help:

☑️ Avoid reinventing the wheel
☑️ Standardize testing and transformation logic
☑️ Speed up project setup with ready-made components

Consider them modular components that make your dbt projects faster and more consistent.

📁1️⃣ Create packages.yml

In your dbt project directory, create a file named packages.yml.

➕2️⃣ Add packages

Inside packages.yml, specify the packages you want to install. One popular package is dbt_utils. This package is a toolkit of pre-built macros and tests that simplifiy and enhance data transformations. To use it, add the following to packages.yml:

packages:
  - package: dbt-labs/dbt_utils
    version: 1.3.0
💡
Always pin versions to avoid breaking changes.

Here you can find other popular dbt packages:

dbt - Package hub
Package hub

⚙️3️⃣ Install Packages

After adding the packages to your packages.yml, run the following command in your terminal:

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