Knowledge graphs have become increasingly popular in recent years, as organizations seek to better manage and leverage their data assets.
By creating a knowledge graph, an organization can represent its data in a structured and semantically rich format that enables powerful analytics, search, and inference capabilities.
However, building a successful knowledge graph is not a trivial task. It requires careful planning, a deep understanding of the organization's data assets, and the right technical capabilities.
The Enterprise Knowledge Graph Maturity Model provides a structured approach to evaluating an organization's progress along the knowledge graph journey. It is designed to help organizations understand the key stages of knowledge graph maturity, from the initial stages of data exploration to the creation of a fully integrated, enterprise-wide knowledge graph.
By following the maturity model, organizations can identify areas for improvement and develop a roadmap for advancing their knowledge graph initiatives.
