Dbt Transformation Patterns
Identifies potential dbt transformation improvements like model duplication, unused columns, and inefficient logic.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add dbt-transformation-patterns npx -- -y @trustedskills/dbt-transformation-patterns
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"dbt-transformation-patterns": {
"command": "npx",
"args": [
"-y",
"@trustedskills/dbt-transformation-patterns"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill provides a collection of transformation patterns for use with dbt (data build tool), enabling users to clean, transform, and model data efficiently. It includes reusable SQL templates and best practices for common ETL tasks such as filtering, joining, aggregating, and deduplicating datasets.
When to use it
- When building complex data pipelines that require standardized transformation logic
- To streamline the development of dbt models by reusing proven patterns
- When working with large or messy datasets that need consistent cleaning and structuring
- For teams looking to enforce best practices in their dbt projects
Key capabilities
- Reusable SQL templates for common transformations
- Best practices for data modeling and ETL workflows
- Support for filtering, joining, aggregating, and deduplicating data
- Compatibility with dbt’s modular architecture
Example prompts
- "Create a dbt model to filter out null values from the user table."
- "Generate a SQL template for joining customer and order tables in dbt."
- "Provide a pattern for aggregating daily sales data using dbt."
Tips & gotchas
- Ensure your dbt project is properly configured before applying these patterns.
- Some templates may require adjustments to match specific database schemas or dialects.
Tags
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