Laura Amaral refactored and improved data correctness for the Br_ibge_censo_2022 dataset in the basedosdados/queries-basedosdados repository. She consolidated fragmented data into new municipio and setor_censitario tables, enhancing organization and long-term maintainability. Her work included removing redundant SQL files to streamline deployment and reduce technical debt. Laura also addressed a column naming issue in the alfabetizacao CTE, ensuring accurate literacy rate processing. Throughout the project, she applied data engineering and data modeling skills, leveraging Python and SQL to implement structural changes. The depth of her contributions focused on schema clarity, data accuracy, and maintainable database architecture within the project.