This thesis addresses the challenge of defining Data Products in a clear and actionable way by developing a comprehensive metadata model. While the concept of Data Products is gaining traction in data-driven organizations, their practical implementation often lacks consistency due to vague definitions. To tackle this, the thesis begins with an analysis of current literature and best practices surrounding metadata models and Data Product concepts. Based on this, key requirements for a metadata model are derived to ensure essential characteristics such as shareability, discoverability, and interoperability. A structured metadata model is then proposed and implemented. Its effectiveness is demonstrated through a real-world use case in an engineering environment. Finally, the model is evaluated against defined requirements, showing how it improves clarity and standardization in Data Product descriptions. The work concludes by outlining future research directions and potential enhancements.