
Katey Matthews contributed to the ONSdigital/monthly-business-survey-results repository by engineering features that improved data quality, reporting accuracy, and analytical reliability. She enhanced the turnover analysis pipeline by cleaning unused columns and aligning test data, reducing processing errors and supporting more robust analytics. In subsequent months, Katey developed a weighted growth rates calculation, applying data weighting and aggregation techniques in Python and Pandas to improve metric comparability. She also delivered devolved nations reporting enhancements, refactoring percentage calculations and extending outputs with time-series support. Her work demonstrated careful data engineering, schema management, and a focus on maintainability, directly addressing business and governance needs.

In August 2025, delivered the Devolved Nations Reporting Enhancement for ONSdigital/monthly-business-survey-results, delivering more accurate devolved nation reporting, improved data integrity, and extended outputs with explicit start/end dates. This work included refactoring of percentage calculations, improved handling of multiple flag values and missing name values, and alignment with reporting requirements to support time-series analysis and governance oversight. The changes reduce data quality risk and enable better business decisions for devolved nations.
In August 2025, delivered the Devolved Nations Reporting Enhancement for ONSdigital/monthly-business-survey-results, delivering more accurate devolved nation reporting, improved data integrity, and extended outputs with explicit start/end dates. This work included refactoring of percentage calculations, improved handling of multiple flag values and missing name values, and alignment with reporting requirements to support time-series analysis and governance oversight. The changes reduce data quality risk and enable better business decisions for devolved nations.
July 2025 monthly summary for ONSdigital/monthly-business-survey-results focusing on key accomplishments, business value, and technical achievements. In July, delivered the Weighted Growth Rates Calculation feature for the Monthly Business Survey Results repo. Introduced weighted_target by weighting adjustedresponse with design_weight, outlier_weight, and calibration_factor, and updated the growth rates aggregation to use weighted_target instead of the raw target. This change enhances accuracy and comparability of growth metrics across cohorts and reduces susceptibility to extreme values. The work is tracked under commit b3e72a738bd0baf6807e9e7c4a3f8922372df7bc (weighted version of target variable in growth rates output and corrections) linked to PR (#251).
July 2025 monthly summary for ONSdigital/monthly-business-survey-results focusing on key accomplishments, business value, and technical achievements. In July, delivered the Weighted Growth Rates Calculation feature for the Monthly Business Survey Results repo. Introduced weighted_target by weighting adjustedresponse with design_weight, outlier_weight, and calibration_factor, and updated the growth rates aggregation to use weighted_target instead of the raw target. This change enhances accuracy and comparability of growth metrics across cohorts and reduces susceptibility to extreme values. The work is tracked under commit b3e72a738bd0baf6807e9e7c4a3f8922372df7bc (weighted version of target variable in growth rates output and corrections) linked to PR (#251).
March 2025 monthly summary for ONSdigital/monthly-business-survey-results. Focused on data quality improvements in the turnover analysis pipeline. Delivered a targeted data-cleanup change that removes unused columns and aligns test data, reducing downstream processing errors and enabling more reliable turnover analytics for stakeholders.
March 2025 monthly summary for ONSdigital/monthly-business-survey-results. Focused on data quality improvements in the turnover analysis pipeline. Delivered a targeted data-cleanup change that removes unused columns and aligns test data, reducing downstream processing errors and enabling more reliable turnover analytics for stakeholders.
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