Delivering better patient outcomes with data-driven insights

A global leader in life sciences was realizing poor performance from their data operations due to the complexity of their IT infrastructure. With over 30 ERPs and data sources, each configured differently to support the varied functions they performed, their architecture was fragmented, slowing data engineering productivity, which was causing delays to the successful operation, management and control of their various supply chains.

While access to raw data was not an issue, creating the data pipelines that would unify, transform, and make sense of the data was a task that was too technical for many on the data engineering team. Intimate knowledge of the data was limited, so the organization needed tooling that could democratize the development of pipeline creation so as to effectively enable team members, regardless of their level of expertise or familiarity with the data itself.

The Prophecy data engineering platform was selected for its ability to seamlessly integrate with their Databricks Lakehouse implementation as well as their complex IT infrastructure and processes, including the more than 30 ERPs and domains, as well as their code management and CI/CD workflows. On the development side, Prophecy’s low-code, visual design and build capabilities are enabling all contributors on their data team to create flexible, highly scalable, and reusable data assets that support supply chain efficiency, from inventory management, and sales orders, to manufacturing operations and more.

The organization has been able to see massive productivity improvements in their data engineering capabilities to where a single segment of their data team can now perform as well as three teams before the implementation of Prophecy. In addition, the quality of the data pipelines being developed have been outstanding, with the code written by Prophecy being on par with the code written by their most senior data engineers.