Giulia Giaccaglia enhanced the ONSdigital/monthly-business-survey-results repository by delivering robust data cleaning improvements focused on data integrity and reliability. She refactored the data cleaning logic in Python, optimizing lambda usage within the run_live_or_frozen function and implementing conditional replacements in correct_values to address edge cases involving the frozen column and NaN values. Giulia updated the associated tests to ensure alignment with the new data processing behavior, supporting ongoing maintainability. Additionally, she resolved pre-commit hook issues, stabilizing the continuous integration workflow. Her work reduced manual validation effort and improved the overall quality and reliability of the monthly business survey data pipeline.