Large enterprises maintain a multitude of data assets pertaining to their businesses. It’s arduous for engineers and data scientists to not only find the information they need, but also to ensure it’s accurate and up to date. This can lead up to data duplication, misuse of assets, and conflicting results. We address this problem by leveraging an enterprise ontology, which we assume users in a domain will intuitively understand. Our approach is novel in that we allow users to navigate over their data assets semantically, using the concepts and relationships of this ontology. We present a case study involving a client that uses an ontology comprising hundreds of concepts to efficiently search for and manage a set of data assets that number in the tens of thousands. This solution uses the RelationalAI Knowledge Graph Management System to power this search process. We include a live demonstration of the working solution and discuss some important lessons learned.