Data Build Tool

This tool targets data engineers and analytics engineers who design, test, and deploy data transformations in modern data stacks. It provides a structured, dbt-like workflow for modeling, testing, and documenting data pipelines. Users include analytics teams at startups to large enterprises seeking repeatable, auditable pipelines and CI/CD readiness. The approach emphasizes modeling as code, lineage, tests, and documentation as living artifacts, enabling teams to governance-first collaboration and faster delivery.
Core capabilities include a DAG-based planner, sources, models, seeds, snapshots, tests, and macro support. Required inputs are source definitions, model configurations, materialization settings, and test definitions; optional features include repository management, multi-warehouse targets, and custom macros. The tool compiles SQL for each warehouse dialect, resolves dependencies, and executes tests to validate correctness, performance, and data quality.
Outputs include compiled SQL, dependency graphs, test results, and documentation artifacts. It generates audit-friendly lineage and changelogs for deployments. Use cases span analytics readiness, BI data models, and data catalog enrichment. Unique value comes from its modular, open-architecture design that mirrors real-world data stacks while enabling CI integration, repeatable deployments, and collaboration across data teams. It supports governance, reproducibility, and faster analytics delivery.