Data modeling is a process of creating conceptual, logical, or physical data models for one’s data.

Life sciences companies accumulate data with an ever-increasing pace, and data that they use to create new treatments or new diagnostics is more diverse and complex than in arguably any other domains. With multiple data sources, data elements, stakeholders, and data consumers, it gets progressively harder and harder to scale and to maintain control over the data life cycle. There is a strong awareness in the scientific community that more data must produce more insight and knowledge, but this goal has been difficult to attain. Life Sciences businesses are now relying on the practice of data management and data governance as best business practices to wrangle data assets and realize value from data.

There are many resources that deliver data management and data governance solutions. There are frameworks, platforms, and solutions; there are tools that one can use and knowledge bases to consult with. We are different. We provide people—scientists with subject matter expertise trained in data modeling—who can help. Our people have dozens of years of experience in their respective fields of study and participated in multiple projects where they did data modeling or provided data governance support. We have real-life experience, and we can support your projects with minimal ramp-up time by leveraging data models we have already built and know-how.