Large SQL scripts can be difficult to read, understand, and maintain. With dbt, you can use the ref function to break down a long SQL statement into smaller components.

Consider this example:

Calculate total order amount:

-- models/total_order_amount.sql
SELECT 
    order_id, 
    customer_id, 
    SUM(order_amount) AS total_amount
FROM
    raw_orders
GROUP BY order_id, customer_id

models/average_order_amount.sql:

-- models/average_order_amount.sql
SELECT 
    customer_id, 
    AVG(total_amount) AS avg_amount
FROM {{ ref('total_order_amount') }}
GROUP BY customer_id

Benefits of this approach:

• Collaboration: Team members can work on separate modules simultaneously.
• Development: Easier to write and debug smaller, focused components.
• Maintenance: Update specific modules without affecting the entire query structure.
• Reusability: Encapsulate common SQL patterns for use across various queries.

By leveraging dbt’s ref function, data teams can transform complex SQL scripts into a series of interconnected, manageable modules. This not only improves code quality but also enhances overall workflow efficiency in data analytics and engineering projects.

Link to dbt.