I co-led a national data science project called Hortianalytics, which analysed more than a decade of New Zealand’s fruit export data to uncover trade patterns and forecast future trends. The project focused on six major horticultural products including kiwifruit, avocados, apples, grapes, oranges, and strawberries, using data from the UN Comtrade database.
I integrated and transformed over 200,000 records using Excel Power Query and Python (Pandas) to ensure clean, reliable data for analysis. I performed statistical inference tests such as t-tests and ANOVA to identify significant differences in export performance across products and countries. Using Power BI, I designed dynamic dashboards for six stakeholder groups such as policymakers, exporters, and trade agencies. These dashboards included visual comparisons of trade volumes, export values, price per kilogram, and trade balance trends from 2013 to 2024.
The project also involved forecasting to 2029 using Python-based time series analysis combined with Power BI visualisation to predict future export growth and market share. The findings highlighted opportunities for export diversification and provided insights for policy planning in the horticulture sector.
This project demonstrates my ability to manage large datasets, apply statistical and predictive methods, and communicate results through interactive dashboards that support strategic decision-making.…I co-led a national data science project called Hortianalytics, which analysed more than a decade of New Zealand’s fruit export data to uncover trade patterns and forecast future trends. The project focused on six major horticultural products including kiwifruit, avocados, apples, grapes, oranges, and strawberries, using data from the UN Comtrade database.
I integrated and transformed over 200,000 records using Excel Power Query and Python (Pandas) to ensure clean, reliable data for analysis. I performed statistical inference tests such as t-tests and ANOVA to identify significant differences in export performance across products and countries. Using Power BI, I designed dynamic dashboards for six stakeholder groups such as policymakers, exporters, and trade agencies. These dashboards included visual comparisons of trade volumes, export values, price per kilogram, and trade balance trends from 2013 to 2024.
The project also involved forecasting to 2029 using Python-based time series analysis combined with Power BI visualisation to predict future export growth and market share. The findings highlighted opportunities for export diversification and provided insights for policy planning in the horticulture sector.
This project demonstrates my ability to manage large datasets, apply statistical and predictive methods, and communicate results through interactive dashboards that support strategic decision-making.WW…