Doctors, Duplicates & Data Disasters: Engineering Reliable Healthcare Intelligence with SAS DATA Step, PROC SQL and R Wrangling Workflows
The World’s Most Famous Doctors Dataset into Analytical Intelligence with Advanced SAS Data Filtering, PROC SQL vs DATA Step, and Modern R Cleaning Frameworks Introduction — When Dirty Data Becomes a Clinical Disaster Imagine a multinational healthcare analytics company preparing a global recognition report on the world’s most famous doctors. The dataset arrives from multiple hospital systems, research foundations, medical conferences, and legacy CSV exports. At first glance, the data looks usable. But once analysts begin processing it, chaos emerges. One doctor has an age of -45. Another has the specialization written as "cardiologist", "CARDIOLOGIST", "Cardio", and "NULL". Duplicate physician IDs appear from merged systems. Dates are stored in multiple formats. Some records have blank regions, while others contain accidental trailing spaces. Now imagine using this corrupted data to build clinical recognition dashboards, hospital...