Data Modeling Best Practices And Pitfalls For Pharma 4.0

By Aron Semle, Chief Technology Officer at HighByte

In ecosystems as complex and varied as life science manufacturing, data modeling may initially seem daunting. To ensure a successful data modeling project, there are many factors that manufacturers must take into consideration. Here, we share best practices that serve as a guideline for commonly encountered challenges and how life sciences manufacturers can overcome them to achieve success in their data modeling projects by leveraging an Industrial DataOps solution.