dataforgoodfr/13_odis
Nov 2025 – Nov 2025
1 Month active
Languages Used
PythonSQLYAML
Technical Skills
API IntegrationData ExtractionPython DevelopmentSQLdata analysisdata extraction
elsa le bihan
PROFILE
Elsa Le Bihan
Elsa Le Bihan enhanced the dataforgoodfr/13_odis repository by developing advanced EPCI presentation and population data models, focusing on data accuracy and usability for analytics. She integrated new data sources such as Melodi and INSEE, refactored SQL aggregations for precise member and population metrics, and aligned gold and bronze models to improve data governance. Using Python, SQL, and dbt, Elsa also authored comprehensive documentation for new fields in the ODIS bronze model, ensuring clarity for downstream users. Her work demonstrated depth in data modeling, API integration, and database management, resulting in a more robust and transparent data pipeline for reporting.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
2
Lines of code
4,256
Activity Months1
Your Network
18 peopleShared Repositories
18
Arthur HavlicekMember
kloudkraftsMember
apibracMember
antoningarMember
gustelleMember
HAMIDI AminMember
Henry D.Member
salma-hnanaMember
Jean-Baptiste-NMember
Work History
November 2025
6 Commits • 2 Features
Nov 1, 2025November 2025 focused on delivering a richer EPCI data model and strengthening data quality. Key features delivered include EPCI Presentation and Population Data Model Enhancements, with new data fields (EPCI codes, population stats), a refactored SQL aggregation for accurate member counts and population metrics, integration of Melodi and INSEE sources, and a new gold model aligned with updated bronze references. Additionally, ODIS Bronze Model Documentation for New Fields was added to improve clarity and usability. In terms of quality and stability, critical fixes were applied to stabilize the pipeline: silver query corrections, API extraction parameter adjustment to remove the 10,000-record limit, and bronze/gold alignment refinements (pre-commit cleanup). These efforts collectively improve data accuracy, timeliness, and usability for downstream analytics and reporting, driving better governance and business decisions.
6 Commits • 2 Features
Nov 1, 2025November 2025 focused on delivering a richer EPCI data model and strengthening data quality. Key features delivered include EPCI Presentation and Population Data Model Enhancements, with new data fields (EPCI codes, population stats), a refactored SQL aggregation for accurate member counts and population metrics, integration of Melodi and INSEE sources, and a new gold model aligned with updated bronze references. Additionally, ODIS Bronze Model Documentation for New Fields was added to improve clarity and usability. In terms of quality and stability, critical fixes were applied to stabilize the pipeline: silver query corrections, API extraction parameter adjustment to remove the 10,000-record limit, and bronze/gold alignment refinements (pre-commit cleanup). These efforts collectively improve data accuracy, timeliness, and usability for downstream analytics and reporting, driving better governance and business decisions.
November 2025
Activity
Loading activity data...
Quality Metrics
Correctness83.4%
Maintainability83.4%
Architecture83.4%
Performance80.0%
AI Usage23.4%
Skills & Technologies
Programming Languages
PythonSQLYAML
Technical Skills
API IntegrationData ExtractionPython DevelopmentSQLdata analysisdata extractiondata modelingdatabase managementdbtdocumentation
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline