Kurt is the founder and CEO of Semantical, LLC, a consulting company focusing on enterprise data hubs, metadata management, semantics, and NoSQL systems. He has developed large scale information and data governance strategies for Fortune 500 companies in the health care/insurance sector, media and entertainment, publishing, financial services and logistics arenas, as well as for government agencies in the defense and insurance sector (including the Affordable Care Act). Kurt holds a Bachelor of Science in Physics from the University of Illinois at Urbana–Champaign.
Having been involved in the Semantic space for more than a decade and a half, I've seen quite a few arguments that seem to be eternal.
Network graphs play a large part in both computing and data science, and they are essential for working with (and visualizing) both semantic graphs and property graphs.
If you have ever had a book self-published through Amazon or similar fulfillment houses, chances are good that the physical book did not exist prior to the order being placed.
Every so often as a writer, you come to the realization that the article that you're working on is going to piss a lot of people off, including friends and colleagues.
If you are a data science type of person, knowledge graphs are really cool.
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