January 2026 monthly summary for dataforgoodfr/13_odis. Delivered seed-based geographic data migration with annual passage validation, cleaned up DBT models and updated INSEE code documentation, and introduced Prefect-dbt integration with improved observability and development environment stability. These changes improved data quality, mapping accuracy for the most recent year, pipeline reliability, and development velocity.

Monthly work summary for 2025-12 focusing on expanding granularity and stabilizing geographic data modeling for dataforgoodfr/13_odis. Key outcomes include broader commune-level household data, new regional and departmental aggregations, and a streamlined gold layer; comprehensive geographic data model modernization with a new COM level and consistent geo codes; and a tightened data pipeline with seed data, tests, and removal of obsolete layers.

November 2025 delivered substantial improvements to population data handling, API usability, and development workflow for dataforgoodfr/13_odis, with a focus on business value, data accuracy, and reliability. Key bug fix and feature work reduced data load failures, improved data fidelity at the commune level, and strengthened testing and documentation to support scalable growth.

October 2025 – Delivered end-to-end data pipelines and quality enhancements for the dataforgoodfr/13_odis project. Implemented a full Commute Travail data pipeline with new source and bronze/silver/gold layers, added INSEE taux_pauvrete data at commune and supra-commune levels, and stabilized dependencies and data quality across the stack. Fixed key upstream/downstream issues, expanded coverage to logement domain data via INSEE inputs, and introduced modeling and casting improvements to improve lineage and reliability. Demonstrated strong automation, testing, and governance, delivering tangible business value with more complete, accurate, and timely insights.

September 2025 — dataforgoodfr/13_potentiel_solaire: Delivered key feature improvements and documentation clarifications to improve solar potential estimation accuracy and maintainability. Analyzed model approaches, added tests, and documented methodology to empower informed decisions.