But what it doesn’t do well is map relationships between many things, so when you try to model a complex organization, it’s really hard to do. If you think about a person, for example, you might ask ...

Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

Dr. Alin Deutsch of UC San Diego explains in a Q&A why graph database algorithms will become the driving force behind the next generation of AI and machine learning apps.

This is why graph databases are a good match in use cases that require leveraging connections in data: Anti-fraud, Recommendations, Customer 360 or Master Data Management.