Graph Data Science Use Cases: Supply Chain Analytics

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Summary

Given the unpredictability of world events and the complexity of modern supply chains, you need advanced analytics to ensure your supply chain management system is agile enough to respond quickly when disaster strikes.

With Neo4j Graph Data Science, you can use the connections in your data to analyze your entire supply chain, gaining otherwise unattainable insights from the relationships in the data you already have.

In this brief paper, you will:

  • Learn three flexible techniques for supply chain analytics
  • See a sample graph data model
  • Find out which graph algorithms to run – and why

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