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dbt-transformation-patterns

data_procNoneIntermediateClaude
🤖 AI Summary

This skill provides reusable dbt project structures and configurations for model layering, testing, documentation, and incremental logic, enabling developers to quickly scaffold production-grade data transformation pipelines.

How to Install

This skill comes from a community source.

dbt Transformation Patterns

Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing.

Use this skill when

  • Building data transformation pipelines with dbt
  • Organizing models into staging, intermediate, and marts layers
  • Implementing data quality tests and documentation
  • Creating incremental models for large datasets
  • Setting up dbt project structure and conventions

Do not use this skill when

  • The project is not using dbt or a warehouse-backed workflow
  • You only need ad-hoc SQL queries
  • There is no access to source data or schemas

Instructions

  • Define model layers, naming, and ownership.
  • Implement tests, documentation, and freshness checks.
  • Choose materializations and incremental strategies.
  • Optimize runs with selectors and CI workflows.
  • If detailed patterns are required, open resources/implementation-playbook.md.

Resources

  • resources/implementation-playbook.md for detailed dbt patterns and examples.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Details

Category Data → data_proc
Sourcecommunity
SKILL.mdView on GitHub →
Repo StarsN/A
Est. per SkillN/A (shared across 1230 skills from this repo)
DifficultyIntermediate
Risk LevelNone

Related Skills

Works Well With

Skills from the same repository — often designed to work together