Why Cross-team model sharing in dbt? - Purpose & Use Cases

The Big Idea

What if your team could stop reinventing the wheel and trust the same data models effortlessly?

The Scenario

Imagine you work in a big company where different teams build their own data models separately. Each team tries to recreate similar calculations and logic on their own, often copying and pasting code from emails or documents.

The Problem

This manual way is slow and confusing. Teams waste time fixing bugs that others already solved. Inconsistent models cause errors and mistrust in data. It's hard to know which version is correct or up to date.

The Solution

Cross-team model sharing lets teams build data models once and share them easily using dbt. Everyone can use the same trusted models, avoiding duplication and mistakes. Updates happen in one place and reflect everywhere automatically.

Before vs After

✗ Before

SELECT revenue FROM sales_team_model;
-- Each team writes their own version

✓ After

SELECT * FROM {{ ref('shared_sales_model') }};
-- Reuse a shared model across teams

What It Enables

It enables smooth collaboration where teams trust and build on each other's work, speeding up data projects and improving accuracy.

Real Life Example

In a retail company, the marketing and finance teams both need customer purchase data. Instead of building separate models, they share a single customer sales model, ensuring consistent reports and faster insights.

Key Takeaways

Manual model duplication wastes time and causes errors.

Sharing models with dbt creates one source of truth.

Teams collaborate better and deliver faster, reliable data.