There are a variety of challenges in biomedical data integration that stand in the way of scientific insights. The variety of data models from lab information systems, lab notebooks, and mountains of excel spreadsheets really undermine the ability to ensure that the right data is in the right place at the right time to answer a question or test a hypothesis. I think it is critical to bring a data-centric mindset, architecture, and model-driven systems into the biotech industry if we are going to produce trustworthy analyses that drive innovation for patients in need.