Fruit Supply Chain Corruption Solved Through SAS & R Automation
Global Fruit Dataset Chaos into Analysis-Ready SAS and R Pipelines for Regulatory-Grade Reporting Excellence Introduction In real-world analytics environments, dirty data is not just an inconvenience it is a direct business risk. I have seen pharmaceutical companies delay clinical submissions because patient visit dates were corrupted. I have seen insurance firms reject valid claims because region codes were inconsistent. I have seen banking fraud systems fail because transaction IDs were duplicated. Now imagine a global fruit-export intelligence platform collecting operational data from multiple countries about rare fruits such as Durian, Rambutan, Mangosteen, Miracle Fruit, Buddha’s Hand, Jabuticaba, Salak, and Ackee. The business wants to combine retail intelligence, shipment quality, healthcare nutrition research, and customer analytics into one centralized reporting system. Unfortunately, the incoming datasets are corrupted. Some fruit shipment IDs are duplicated. Some su...