The Metadata Knowledge Graph

Modern data landscapes are characterized by immense volumes of diverse, disparate, and dynamic data sources, leaving many organizations struggling to effectively manage and derive value from their data assets. To address these challenges, a metadata knowledge graph serves as a valuable tool for metadata management in the semantic layer, as it enables organizations to easily identify and contextualize what kind of data they have across their information ecosystems. A particular application of an enterprise knowledge graph, a metadata knowledge graph provides a structured way to organize, connect, and understand knowledge and data assets with corresponding data provenance and usage information for an end-to-end view of organizational data.  While an enterprise knowledge graph encompasses all data entities and actual data instances across an organization, a metadata knowledge graph specifically focuses on gathering and managing metadata, or information about data entities, attributes, relationships, and their context. Aggregating and surfacing contextual information in the form of metadata – from what data is collected to how it is consumed – ultimately supports data accessibility, findability, traceability, connectivity, governance, and understanding across the enterprise.