Using pre-hooks in dbt: A Hands-On Guide

📘Introduction

In this hands-on dbt tutorial, you'll learn how to use pre-hooks to automate tasks such as creating backup tables before a model runs. Pre-hooks allow you to execute SQL before your dbt model builds, which is useful for auditing, data quality checks, or preparing the environment.

✅ Prerequisites

☑️ A dbt project set up
☑️ Source data loaded into your data warehouse
☑️ Source configurations defined in sources.yml

💡 What are pre-hooks in dbt?

A pre-hook is SQL that runs automatically before a model executes.
They are commonly used for:

• Backing up tables
• Cleaning or truncating tables
• Logging metadata or audit information
• Enforcing data quality checks

In a dbt project pre-hooks can be defined:

• Inside a model file using a config block.
• Inside a seed or snapshot configuration YAML.
• In dbt_project.yml for models, seeds, and snapshots.

🧠 Practical Example

Let’s walk through an example. Let's consider a dbt model called student that looks like this:

SELECT * FROM {{ ref("dim_student") }}

This simply selects all data from the dim_student table. In the warehouse, you can see that the table already exists.

🧙 Now, want to create a pre-hook that makes a backup of the table before the model runs.

⚙️1️⃣ Add pre-hook to your SQL code

Inside your model SQL file (models/student.sql), add a config block at the top: