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
Connect and model industry systems and processes for deeper data-driven insights in:
Improve engagement, discoverability and personalized recommendations for Financial and Business Media, Market Intelligence and Investment Information Agencies, Science, Technology and Medicine Publishers, etc.
Historically, the enterprise data management market has been split into operational and analytical software products, followed by an extensive list of derivative solutions like data warehouses, data lakes, lake houses, etc., aiming to fix the connection between these two worlds.
Knowledge graphs are a new way of thinking where teams shift from software-driven development to data-driven development. The leading technology teams aim to develop critical graph models that serve analytical or operational use cases and ensure maximum interoperability with no human intervention.
This talk shares some of the latest technology trends and points you to important knowledge graph technology patterns.