SUBHRANSU PANI

Across industry, data is growing exponentially—yet decisions are still slow, manual, and fragmented. Teams spend more time reconciling numbers than acting on them, and many AI initiatives stall because the data foundation isn’t ready.In Pharma R&D, this challenge is amplified. Our data spans internal systems, CROs, investigator sites and partners—within a highly regulated, time-sensitive environment where delayed insight can mean delayed medicines for patients.In this session, we’ll share how we reframed data strategy as decision strategy. Within a year, we built a trusted, scalable foundation powering R&D, Finance, and TechOps—enabling faster portfolio prioritization, improved clinical visibility, smarter resource allocation, and AI readiness by design.Through real R&D use cases, we’ll show how reusable data products, embedded governance, and a modern Databricks architecture turned fragmented data into decision-ready intelligence.