Knowledge graphs are powering more artificial intelligence (AI) apps than ever.
That’s because they have the ability to overcome many of the data integration challenges that pose a significant barrier to widespread AI adoption.
According to Gartner, “Data and analytics leaders looking to deploy AI in the enterprise should start with knowledge graphs that enable targeted use cases to demonstrate the potential of this technology.”
The report provides data and analytics leaders with best practices in:
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- Initiating knowledge graph projects from a business-driven perspective
- Methods to move from proofs of concept (POCs) to real-world applications
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Gartner, How to Build Knowledge Graphs That Enable AI-Driven Enterprise Applications, Afraz Jaffri, 27 May 2020
The above graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Neo4j.