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SQL is powerful — but without the right tooling, every pipeline change becomes a manual, error-prone nightmare.
The Analytics Reality
The Problem
Pain Points for SQL-Centric Users
— Without dbt
Weak or Missing Lineage
Hard to see which tables feed others
No auto-generated dependency graph
No State-Aware Runs
Every change triggers a full rebuild
Wastes compute and increases cost
No Built-in Testing
Must write ad-hoc SQL to check quality
No standard place to store or run tests
Inconsistent Documentation
Column definitions documented inconsistently
New team members must reverse-engineer logic
