About this episode
With the hype of graph databases and knowledge graphs, a common (mis)practice is to quickly migrate your existing siloed data into a graph database. But be careful! You may just be bringing the complexity of your silos into the graph.
Join Tim, Juan and guest Jans Aasman from Franz Inc, the makers of AllegroGraph, for a conversation on why your graph-based machine learning and 360 projects should start with data modeling.
This episode features
Data modeling approaches you should consider
Tips to avoid data modeling pitfalls
If you could be a top model for any product/brand, what would it be and why?
It's "terrible" to start creating an ontology without knowing the application
Intelligent people make the schemas… this is not easy
Modeling is human problem solving!