A knowledge graph is a design pattern that can help users better understand data.  A graph is formed of nodes and relationships:

• a node is a person, object, location, or event
• relationship refers to the interaction among nodes.

Representing data to depict these connections (relationships among nodes) can enhance the value of information.

According to Wikipedia, the Knowledge Graph was launched by Google in May 2012 to enhance the value of information returned through Google searches. By May 2016, knowledge boxes appeared for some one-third of the 100 billion monthly searches the company was processing.  The Google Knowledge Graph depicts relevant information in an infobox next to its search results. This enables users to see the answer in a glance. Data is generated automatically from multiple sources, and it covers places, people, organizations, and more.

Knowledge graphs are at the core of human-facing technologies such as search, question answering, dialogue, and recommenders.  They are particularly useful in fields characterized by data silos (e.g., healthcare and financial services). Knowledge graphs can help with data governance, fraud detection, knowledge management, searches, chatbot use, developing recommendations, and developing intelligent systems across different organizational units.