Challenges in Data Quality and Context for Data Scientists in the Pharmaceutical Industry

The chapter addresses the frustration of data scientists in the pharmaceutical industry regarding the lack of context in data collected for various applications, hindering effective machine learning tools. It highlights the challenges faced by traditional pharmaceutical companies in maintaining data quality despite heavy investment in AI tools, discussing the need for positive incentives to improve data quality. The chapter also touches on the shift in perception towards short-term solutions rather than long-term value creation in data science, emphasizing the importance of building products beyond just models.