AstraZeneca’s future digital ambitions require unlocking the potential of data and AI to accelerate and innovate drug development. However, to enable AI @ scale you need a solid data foundation. Central to this vision is the evolution from fragmented data silos to a robust, scalable approach for building and deploying data products. In this session, we explore what constitutes a data product for AstraZeneca, and how our journey began with significant challenges: a complex data mess exacerbated by regulatory pressures, isolated working models, and traditional waterfall development methods. 

We will explore the solutions that drove transformation, including a new operating model, rapid prototyping methods, and the implementation of DataOps.live on Snowflake. These changes have drastically cut the time needed to deliver a data product, reducing it from 4-6 months to just 4-6 days. This swift progress is unlocking significant business value and revolutionizing team collaboration across the organization.

Looking ahead, AstraZeneca is poised to expand these foundations by embracing knowledge graphs and scalable AI solutions, further amplifying the impact of data products on drug development, and operations.