In a world with drastically evolving regulatory requirements, corporations of all sizes are facing the challenge of adjusting both their business processes and risk management practices. Companies with decentralized, multi-layered structures and huge customer bases inherit a constant regulatory demand for risk control and network transparency on a large scale
Knowledge graphs are adept at mapping complex, interconnected data and maintaining high performance with vast volumes of data. Their relationship-centric approach makes them the perfect technology for building a digital twin.
In this webinar, you’ll learn how to create a functional prototype based on the Neo4j graph database for supply chain risk management which we jointly created with Siemens AG. Join us to find out:
- What a knowledge graph is and how to use it for your digital twin
- How to identify bottlenecks and perform “what if” scenarios in the knowledge graph
- Examples of supply chain risk management being used for data discovery in the supply chain
- How to enable mult-tier visibility / transparency of the supply chain for early detection and mitigation of risks in increasingly fragile supply chains
Don’t miss this 120-minute session with Josef Aberham, Cloud Solution Architect at Siemens AG and Alexander Katzdobler, Technical Field Engineering at Neo4j, where you’ll get a demo of how to build a first functional prototype to support risk management of the supply chain.
Josef Aberham has several years of experience as a Service Manager, Project Manager and Senior Consultant at Siemens within various areas of IT. He recently certified as AWS Cloud Architect. His professional focus in the past was SAP Consultant.
Alexander Katzdobler is part of the Technical Field Engineering team at Neo4j. As a technical contact he helps with product decisions and supports our customers in onboarding with Neo4j. IT project management, technical sales and IT consulting were his professional focus in the past.
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