A knowledge graph as it relates to individual organizations is a unification of information across that organization enriched with contextual and semantic relevance. Introducing a knowledge graph creates a comprehensive and baseline set of knowledge accessible by personnel, applications and customers alike to gain understanding and drive actions and direction.
This foundational knowledge graph is not only useful for people and applications, but provides a relevant and evolving dataset for sophisticated learning and intelligence software systems to utilize in providing personalized internal guidance as well as highly engaging interactions with customers.
The main result from this approach is a complex infrastructure containing data silos filled with duplicated, expired, and redundant information. This makes it hard to see the right information and acquire important insights. Organizations today need a graph data platform to support increasingly complex data management needs; deal with information flow, data infrastructure and communication problems; and allow next-generation systems to effectively seek, share, filter, and review data.
Providing a way for people and systems to connect and leverage a holistic perspective of this knowledge that exists perpetuates better insights and decision making by your subject matter experts because they understand more of business as a whole. Advancing enterprises are those that are bringing this knowledge out of isolation from within a single group or department and connecting it enterprise-wide.