Production-grade R Shiny Dashboards for Data Quality

Context: Global commodity pricing platform requiring real‑time data quality monitoring for 40,000+ live price points across 12 commodity categories.

Challenge: Manual quality checks were slow and error‑prone. Needed production-grade dashboards that could handle high volumes, enforce data integrity, and scale across 600+ editorial users.

Solution: Architected a suite of R Shiny dashboards using:

• Golem architecture – enforced modular, standardized design patterns across all applications
• Unit testing with devtools, shinytest2, and testthat for reliability
• CI/CD pipelines via GitHub Actions for automated deployment
• Deployed on Posit Connect for enterprise‑wide access

Outcome: Provided real‑time visibility into data quality, reduced manual oversight, and gave the editorial team confidence in the accuracy of every published price.