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In this session, we take a look at graph database technology within manufacturing in general, and more specifically in the automotive industry.
We review the types of data that are typically available within a manufacturing company, illustrate some automotive-specific graph data models, and discuss the use cases those data models enable and transform. The use cases presented include bills of materials (BOM), supply chain management, logistics and claims processing.
We also discuss where graph algorithms and integration with artificial intelligence (AI) and machine learning technologies are used alongside Neo4j to unlock new value from manufacturing data.
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