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A tartalmat a Connected Data World biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Connected Data World vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
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The future of AI in the Enterprise: Entity-Event Knowledge Graphs for Data-Centric Organizations | Jans Aasman

37:22
 
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Manage episode 303823998 series 2773575
A tartalmat a Connected Data World biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Connected Data World vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

Personalized medicine. Predictive call centers. Digital twins for IoT. Predictive supply chain management, and domain-specific Q&A applications.

These are just a few AI-driven applications organizations across a broad range of industries are deploying.

Graph databases and Knowledge Graphs are now viewed as a must-have by Enterprises serious about leveraging AI and predictive analytics within their organization.

Franz Inc. is helping organizations deploy novel Entity-Event Knowledge Graph Solutions to gain a holistic view of customers, patients, students or other important entities, and the ability to discover deep connections, uncover new patterns and attain explainable results.

To support ubiquitous AI, a Knowledge Graph system will have to fuse and integrate data, not just in representation, but in context (ontologies, metadata, domain knowledge, terminology systems), and time (temporal relationships between components of data).

Building from ‘Entities’ (e.g. Customers, Patients, Bill of Materials) requires a new data model approach that unifies typical enterprise data with knowledge bases such as industry terms and other domain knowledge.

Entity-Event Knowledge Graphs are about connecting the many dots, from different contexts and throughout time, to support and recommend industry-specific solutions that can take into account all the subtle differences and nuisances of entities and their relevant interactions to deliver insights and drive growth.

The Entity-Event Data Model we present puts core entities of interest at the center and then collects several layers of knowledge related to the entity as ‘Events’.

Franz Inc. is working with organizations across a broad range of industries to deploy large-scale, high-performance Entity-Event Knowledge Graphs that serve as the foundation for AI-driven applications for personalized medicine, predictive call centers, digital twins for IoT, predictive supply chain management and domain-specific Q&A applications—just to name a few.

Here's why Entity-Event Knowledge Graphs are the future of AI in the Enterprise.

---

Connected Data London 2024 has been announced!.

December 11-13, etc Venues St. Paul’s, City of London

Check #CDL24 for more Presentations, Keynotes, Masterclasses, and Workshops on cutting-edge topics from industry leaders and innovators: https://connected-data.london

  continue reading

37 epizódok

Artwork
iconMegosztás
 
Manage episode 303823998 series 2773575
A tartalmat a Connected Data World biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Connected Data World vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

Personalized medicine. Predictive call centers. Digital twins for IoT. Predictive supply chain management, and domain-specific Q&A applications.

These are just a few AI-driven applications organizations across a broad range of industries are deploying.

Graph databases and Knowledge Graphs are now viewed as a must-have by Enterprises serious about leveraging AI and predictive analytics within their organization.

Franz Inc. is helping organizations deploy novel Entity-Event Knowledge Graph Solutions to gain a holistic view of customers, patients, students or other important entities, and the ability to discover deep connections, uncover new patterns and attain explainable results.

To support ubiquitous AI, a Knowledge Graph system will have to fuse and integrate data, not just in representation, but in context (ontologies, metadata, domain knowledge, terminology systems), and time (temporal relationships between components of data).

Building from ‘Entities’ (e.g. Customers, Patients, Bill of Materials) requires a new data model approach that unifies typical enterprise data with knowledge bases such as industry terms and other domain knowledge.

Entity-Event Knowledge Graphs are about connecting the many dots, from different contexts and throughout time, to support and recommend industry-specific solutions that can take into account all the subtle differences and nuisances of entities and their relevant interactions to deliver insights and drive growth.

The Entity-Event Data Model we present puts core entities of interest at the center and then collects several layers of knowledge related to the entity as ‘Events’.

Franz Inc. is working with organizations across a broad range of industries to deploy large-scale, high-performance Entity-Event Knowledge Graphs that serve as the foundation for AI-driven applications for personalized medicine, predictive call centers, digital twins for IoT, predictive supply chain management and domain-specific Q&A applications—just to name a few.

Here's why Entity-Event Knowledge Graphs are the future of AI in the Enterprise.

---

Connected Data London 2024 has been announced!.

December 11-13, etc Venues St. Paul’s, City of London

Check #CDL24 for more Presentations, Keynotes, Masterclasses, and Workshops on cutting-edge topics from industry leaders and innovators: https://connected-data.london

  continue reading

37 epizódok

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