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In this post, we dive into how data algebra principles can be applied to the construction of knowledge graphs and knowledge bases—ensuring that business context, workflows, and manufacturing data are structured with maximum efficiency and minimal redundancy.
By treating data relationships algebraically, we can unify fragmented systems, streamline semantic modeling, and prepare clean, scalable knowledge representations that are optimized for vector search, reasoning, and future AI applications.
Stay tuned for the upcoming release of this post.