The paper explores the concept of Data mesh, a change in thinking in data architecture that enables efficient data sharing and creation of data products. The paper emphasizes the significance of data governance, promoting the creation of a data catalog as a central repository for information about data products. The paper introduces the guiding principles of Data mesh are outlined, including a domain-driven approach, product-based thinking, decentralized ownership, and federated governance. The paper further explores the data product lifecycle, detailing the stages from data product initiation to decommissioning or refinement. Additionally, the role of the data catalog in the data mesh is discussed, encompassing components such as data shop, identity management, enterprise knowledge graph, data quality, data dictionary, business glossary, and data lineage.

A large number of business users, data scientists and analysts demand an easy, seamless and ideally self-service way to find and understand data, as it is inefficient to constantly analyze changing data and data schemas and spend time negotiating with technical data stewards who have the knowledge in which system the required data is located and in which schemes and how to request this data so that it can be used to solve business cases. This forces organizations to implement solutions to manage metadata in order to be able to understand their data and data landscape. This research addresses the demand to design an architecture model for the design and implementation of a metadata management tool. The contribution of this paper is the design of a conceptual architecture model of the Metadata management tool, and a process to extract metadata from a data source to provide information about data in a form that is presentable and understandable to users.