Language:
English
Pages:
1 online resource (85 pages)
Edition:
1st edition
Keywords:
Electronic books ; local
Abstract:
Applying knowledge in the right context is the most powerful lever businesses can use to become agile, creative, and resilient. Knowledge graphs add context, meaning, and utility to business data. They drive intelligence into data for unparalleled automation and visibility into processes, products, and customers. Businesses use knowledge graphs to anticipate downstream effects, make decisions based on all relevant information, and quickly respond to dynamic markets. In this report for chief information and data officers, Jesus Barassa, Amy E. Hodler, and Jim Webber from Neo4j show how to use knowledge graphs to gain insights, reveal a flexible and intuitive representation of complex data relationships, and make better predictions based on holistic information. Explore knowledge graph mechanics and common organizing principles Build and exploit a connected representation of your enterprise data environment Use decisioning knowledge graphs to explore the advantages of adding relationships to data analytics and data science Conduct virtual testing using software versions of real-world processes Deploy knowledge graphs for more trusted data, higher accuracies, and better reasoning for contextual AI Applying knowledge in the right context is the most powerful lever businesses can use to become agile, creative, and resilient. Knowledge graphs add context, meaning, and utility to business data. They drive intelligence into data for unparalleled automation and visibility into processes, products, and customers. Businesses use knowledge graphs to anticipate downstream effects, make decisions based on all relevant information, and quickly respond to dynamic markets. In this report for chief information and data officers, Jesús Barassa, Amy E. Hodler, and Jim Webber from Neo4j show how to use knowledge graphs to gain insights, reveal a flexible and intuitive representation of complex data relationships, and make better predictions based on holistic information. Explore knowledge graph mechanics and common organizing principlesBuild and exploit a connected representation of your enterprise data environmentUse decisioning knowledge graphs to explore the advantages of adding relationships to data analytics and data scienceConduct virtual testing using software versions of real-world processesDeploy knowledge graphs for more trusted data, higher accuracies, and better reasoning for contextual AI
Note:
Online resource; Title from title page (viewed July 30, 2021)
,
Mode of access: World Wide Web.
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