Data Transformation Fitness Checker

Adds fitness functions to dbt projects, automatically blocking DAG violations, oversized models, and duplicate logic in CI

Problem

As data transformation projects scale, DAG violations, a single model ballooning to 2,000 lines, and duplicated logic creep in silently. Teams know which direction the project should evolve, but lack automated rules continuously enforced in CI and rely on manual review.

Solution

Provide configurable fitness functions (model line limits, DAG layer constraints, duplicate SQL fragment detection) as a CLI and GitHub Bot wired into CI. Each PR gets an automatic check and a readable report; rule files are versioned with the repo.

Users

dbt-based data teams, analytics engineers, and data platform engineers

MVP

CLI reads dbt project metadata; 5–8 built-in rules (line count, DAG layers, duplicate fragments); one-click GitHub Action; PR comment with violation details; rule config file

Revenue

Free open-source CLI; subscription for the GitHub Bot and team rule sets per repo (e.g., $20–50/month); enterprise self-hosted edition

Why now

dbt has become the de facto standard for data transformation, and governance needs become clear as teams scale. A solo developer can build a rule engine on dbt metadata quickly without massive data.