Provide consistent unified access to data across different systems by using the flexible and semantically precise structure of the knowledge graph model
Implement a Connected Inventory of enterprise data assets, based on a knowledge graph, to get business insights about the current status and trends, risk and opportunities, based on a holistic interrelated view of all enterprise assets.
Quick and easy discovery in clinical trials, medical coding of patients’ records, advanced drug safety analytics, knowledge graph powered drug discovery, regulatory intelligence and many more
Make better sense of enterprise data and assets for competitive investment market intelligence, efficient connected inventory management, enhanced regulatory compliance and more
Improve engagement, discoverability and personalized recommendations for Financial and Business Media, Market Intelligence and Investment Information Agencies,Science, Technology and Medicine Publishers, etc.
Connect and improve the insights from your customer, product, delivery, and location data. Gain a deeper understanding of the relationships between products and your consumers’ intent.
This document is part of the Information Literacy series for Executives
The objective of this industry study was to capture baseline statistics on the size, nature and direction of data management using semantic standards or in other words the capabilities that result from having a knowledge graph.
What does “Knowledge Graph Industry Survey Report” include?
Benchmarking Profiles
Maturity, Drivers, Use Cases and Inhibitors
Industry Capabilities
Key Takeaways
About the author: Michael Atkin has been an analyst and advocate for data management since 1985. His experience spans from the foundations of the information industry to the adoption of semantic technology. He has served as an advisor to financial institutions, global regulators, publishers, consulting firms and technology companies.
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