| name | dbt-transformation-patterns |
| description | Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices. |
dbt Transformation Patterns
Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing.
When to Use This Skill
- Building data transformation pipelines with dbt
- Organizing models into staging, intermediate, and marts layers
- Implementing data quality tests
- Creating incremental models for large datasets
- Documenting data models and lineage
- Setting up dbt project structure
Core Concepts
1. Model Layers (Medallion Architecture)
sources/ Raw data definitions
↓
staging/ 1:1 with source, light cleaning
↓
intermediate/ Business logic, joins, aggregations
↓
marts/ Final analytics tables
2. Naming Conventions
| Layer | Prefix | Example |
|---|
| Staging | stg_ | stg_stripe__payments |
| Intermediate | int_ | int_payments_pivoted |
| Marts | dim_, fct_ | dim_customers, fct_orders |
Quick Start
name: "analytics"
version: "1.0.0"
profile: "analytics"
model-paths: ["models"]
analysis-paths: ["analyses"]
test-paths: ["tests"]
seed-paths: ["seeds"]
macro-paths: ["macros"]
vars:
start_date: "2020-01-01"
models:
analytics:
staging:
+materialized: view
+schema: staging
intermediate:
+materialized: ephemeral
marts:
+materialized: table
+schema: analytics
# Project structure
models/
├── staging/
│ ├── stripe/
│ │ ├── _stripe__sources.yml
│ │ ├── _stripe__models.yml
│ │ ├── stg_stripe__customers.sql
│ │ └── stg_stripe__payments.sql
│ └── shopify/
│ ├── _shopify__sources.yml
│ └── stg_shopify__orders.sql
├── intermediate/
│ └── finance/
│ └── int_payments_pivoted.sql
└── marts/
├── core/
│ ├── _core__models.yml
│ ├── dim_customers.sql
│ └── fct_orders.sql
└── finance/
└── fct_revenue.sql
Detailed patterns and worked examples
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
Best Practices
Do's
- Use staging layer - Clean data once, use everywhere
- Test aggressively - Not null, unique, relationships
- Document everything - Column descriptions, model descriptions
- Use incremental - For tables > 1M rows
- Version control - dbt project in Git
Don'ts
- Don't skip staging - Raw → mart is tech debt
- Don't hardcode dates - Use
{{ var('start_date') }}
- Don't repeat logic - Extract to macros
- Don't test in prod - Use dev target
- Don't ignore freshness - Monitor source data