Emma David refactored the analytics notebook for the dataforgoodfr/13_pollution_eau repository, focusing on improving code readability and maintainability. She restructured SQL queries and Python list definitions, standardizing the formatting of multi-line strings to clarify data retrieval and filtering logic. By prioritizing code quality over bug fixes, Emma reduced technical debt and set the groundwork for faster future iterations and easier onboarding of analysts. Her work leveraged Python and SQL, applying data analysis and code refactoring skills to enhance the reliability and clarity of the analytics workflow, ultimately supporting more efficient collaboration and ongoing development within the project.