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Comment by nemo44x | Hacker News Reader

What's great about knowledge graphs and property graphs in general is once you really get it (and it's not too difficult, especially if you come from a CS background) you start to see graphs all over the place. It's a really nice way to work with data for certain classes of problems. Once you get "enough" data in and "enough" of a variety of things connected, you start to see remarkable relationships emerge.

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What sort of relationships have you seen in the data you've worked with that you'd describe as remarkable?

I've explained a similar thing to friends before, but I was always at a loss for relationships/insights that have led to concrete outcomes

You know active directory? It's basically a graph of objects, accounts and computers all with their own complex permissions and relationships. During pentests it's VERY common to use a tool called bloodhound which imports an active directory graph into neo4j. You then use graph algorithms to find miss configuration and paths to traverse to become domain admin, which pretty much always reveals something "unexpected".

https://github.com/BloodHoundAD/BloodHound

Supply chain and logistics. We’d start to see where the biggest risk points were and use that to diversify risk and also rank failover. We could make predictions about how the supply chain would be disrupted based on individual suppliers/movers/warehouses/etc having events that affected their ability to perform. You start to see how much some suppliers rely on each other, etc. Holy hell did Covid make that crazy!

I think anything that has physical {nodes} and {edges}, where all things in each category are alike but very distinct from the other category, and connectivity is only achievable via a limited set of (not free) paths.

E.g. telecom networks, electrical grids, travel networks (including logistics), etc.

All of these feature a very different node (usually a system or capital asset) vs an edge (usually a wire or constructed path), and insight into the structure is economically valuable.

(That's talking to more traditional uses of graph theory, less-so to modern knowledge graphs)

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