February 2025 monthly summary for dataforgoodfr/13_pollution_eau: Key feature delivered: - Prelevements Uniques DBT Model for Deduplication. Introduced an intermediate table int_prelevements_uniques to identify and select unique prelevement records. The model filters prelevements to those linked to a reseau without reseau_amont and uses a window function to assign row numbers per referenceprel, enabling deduplication and stronger data integrity for analytics. Main commit: - bb953a687fecec0fb72ea177b4fb8525da105143 (Create prelevements uniques table) Major bugs fixed: - none reported this month; effort focused on feature delivery and data quality improvements. Overall impact and accomplishments: - Significantly improved data quality for analytics by ensuring unique prelevement records, which underpins reliable pollution network reporting. - Enhanced ETL reliability and consistency in analytics-ready datasets, reducing downstream reconciliation work. - Strengthened foundation for accurate KPI reporting and data-driven decisions related to pollution monitoring. Technologies/skills demonstrated: - DBT modeling and SQL development - Advanced SQL window functions for deduplication - Data quality and integrity improvements in ETL pipelines - Version control traceability through commit bb953a687fecec0fb72ea177b4fb8525da105143