Global Airports, Hidden Data Corruption & Enterprise Recovery: Building Trusted Aviation Intelligence Using SAS DATA Step, PROC SQL and R
Large Airports in the World Data into Enterprise-Grade Analytics Using SAS (PROC SQL vs DATA Step) and Modern R Engineering Frameworks Introduction: When Dirty Airport Data Becomes a Business Disaster Imagine a global aviation analytics company preparing a regulatory traffic report for international aviation authorities. The dashboard shows passenger growth for major airports across the world. Executives use these reports for expansion planning, runway investments, fuel allocation, and international route approvals. Suddenly, the company discovers catastrophic reporting failures: Duplicate airport IDs inflated passenger counts. Negative cargo volumes appeared in financial reports. Invalid opening dates broke time-series forecasting. Mixed region labels (“asia”, “ASIA”, “Asia-Pacific”) fragmented analytics. Corrupted email addresses failed automated airport communication systems. Missing latitude values crashed AI route optimization mode...