The success or failure of a pharmaceutical product is determined during the first months in the market. Business questions come from all over the organization on a monthly, weekly, daily, and even hourly rate. Analytics plays a key role in providing insights that determine the product’s lifetime revenue. Yet, analytic teams’ biggest struggle is to keep up with customer requests and to avoid letting data errors slip into production. Come learn how this pharmaceutical company used DataOps to improve cycle time (from weeks to one day), reduce errors (to virtually zero), and build a billion-dollar product success.