From Graph to Knowledge Graph: Actioning vs. Decisioning Knowledge Graphs

Unleashing the power of knowledge is crucial for enterprises seeking a competitive edge, as turning data into knowledge remains an ongoing effort despite progress. Enterprises can benefit from connecting their data to create manageable and useful insights by starting small and gaining immediate value before expanding outward. Data management is an important use case for knowledge graphs, enabling companies like Lyft and Airbnb to thrive on data and identify customers in danger of churning or recommending personalized offers. Knowledge graphs form the foundation of modern data and analytics, capturing inherent relationships in data and unlocking predictive power through graph queries and algorithms. These insights can be applied to decisioning, where ultimate goals are to make better decisions whether human or algorithmic, and Neo4j offers a comprehensive solution for building actioning and decisioning knowledge graphs.