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Rethinking EA Mapping: Building a Business-Friendly Mapping Capability with DuckDB, Python, and Notion
From documentation to execution: how to reinvent EA Mapping with modern tools for business-friendly, metadata-driven data engineering.
Summary
Enterprise Architect (EA) Mapping from Bellekens provides a free and open-source way to manage mappings between models inside Enterprise Architect. It supports many-to-many mappings, mapping logic documentation, CSV export/import, and even COBOL copybook imports. While conceptually aligned with model-driven data engineering and business-friendly mapping, its practical use is limited by its dependency on Enterprise Architect, a tool that is often too technical and closed for the modern data stack.
This raises a natural question:
What if we could build an EA Mapping–like capability directly on the modern data stack — with DuckDB, Python, and Notion — so that it aligns with metadata-as-data, business-friendly mapping, and executable pipelines?
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