An advanced analytics platform that processes doctors' prescriptions for 2024 and 2025, calculating total and yearly volume for Sun Pharma, the fourth largest global specialty generic pharmaceutical company with presence in over 100 countries.
The challenge: Sun Pharma, a global pharmaceutical leader operating in 100+ countries, needed to revolutionize how medical professionals accessed prescription data and forecasts. The challenge: build a system significantly faster than their current Excel-based workflow while migrating years of existing data. Doctors required instant mobile access to prescription lookups and medical forecasts, but their legacy Excel system was slow, cumbersome, and difficult to query on mobile devices.
Deep analysis of Sun Pharma's Excel-based prescription system: data structure analysis, query patterns used by medical professionals, mobile usage requirements, and performance bottlenecks. Assessment of migration complexity from legacy Excel files.
Architecture focused on speed: optimized database schema for instant prescription lookups, mobile-first interface for quick access, advanced search and filtering system, forecast visualization dashboard. Python-based data migration pipeline using specialized Excel reading libraries to preserve data integrity.
Phased Excel data migration using Python scripts with specialized libraries for reading and transforming legacy data. Zero downtime migration with complete data validation. System deployed with instant query capabilities, replacing the slow Excel workflow with sub-second response times.
Mission Equipment
Next.js
React
Golang
PostgreSQL
Python
