Data mesh patterns with dbt

Introduction

Data mesh helps teams share and manage data easily across an organization. Using dbt makes building and organizing data models simple and clear.

When different teams own different parts of data and want to share clean data.

When you want to build data models that are easy to understand and update.

When you want to automate data transformations and keep data quality high.

When you want to track changes and test data models automatically.

When you want to create a clear structure for data ownership and access.

Syntax

dbt

model_name.sql
-- SQL code for transforming data

models/
  └─ model_name.sql

dbt_project.yml
-- Configuration file for dbt project

schema.yml
-- File to define tests and documentation

dbt uses simple SQL files to build data models step-by-step.

Each model is a SQL file that creates a table or view in your data warehouse.

Examples

This model filters completed orders from raw data.

dbt

-- models/orders.sql
select * from raw.orders where status = 'completed'

This model selects basic customer info for sharing.

dbt

-- models/customers.sql
select id, name, email from raw.customers

This schema.yml file adds tests to check order IDs are unique and not empty.

dbt

version: 2
models:
  - name: orders
    description: 'Cleaned orders data'
    tests:
      - unique:
          column_name: id
      - not_null:
          column_name: id

Sample Program

This example creates a sales summary model using the orders model. It also adds tests to ensure customer IDs are valid and linked to the customers table.

dbt

-- models/sales_summary.sql
select
  customer_id,
  count(*) as total_orders,
  sum(amount) as total_amount
from {{ ref('orders') }}
where order_date >= '2024-01-01'
group by customer_id

-- schema.yml
version: 2
models:
  - name: sales_summary
    description: 'Summary of sales by customer'
    tests:
      - not_null:
          column_name: customer_id
      - relationships:
          column_name: customer_id
          to: ref('customers')
          field: id

Important Notes

Use {{ ref('model_name') }} to link models and build dependencies.

Tests help catch data problems early and keep data reliable.

Organize models by domain to match data mesh ownership.

Summary

Data mesh patterns help teams share clean, trusted data.

dbt makes building and testing data models easy with SQL files.

Use refs and tests to connect models and ensure data quality.