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Coffee is not only a beloved beverage worldwide but also a vital source of income for millions of smallholder farmers, especially across Asia. However, structural biases in trade networks often result in unequal market access, limiting fair opportunities. This session demonstrates how the <strong>upcoming SQL/PGQ capabilities in PostgreSQL</strong> and the <strong>standardizing Graph Query Language (GQL) for graph databases</strong> can be applied to real-world coffee trade data to detect bias, visualize unfair market structures, and enhance transparency and fairness. Using open datasets from international organizations and NGOs, we will present hands-on query examples, reveal patterns of bias, and discuss practical methods for addressing inequities. Participants will leave with reproducible PostgreSQL queries and a practical framework for applying graph analysis to social impact challenges.
