The Graph Semantics are a new feature of Kusto. It allows users to model their data as graphs and perform graph queries and analytics using the Kusto Query Language (KQL). It supports various graph types, such as directed, undirected, weighted, and labelled graphs, and provides a set of graph operators and functions.

The Graph Semantics can help users gain deeper insights into complex datasets that have inherent or implicit relationships among the data entities. It can also help users discover hidden patterns, anomalies, and communities in their data, as well as measure the importance and influence of different entities. Examples of use cases that can benefit from the graph semantics extension are social network analysis, fraud detection, recommendation systems, cybersecurity, and more.

We are proud to announce that the Kusto Graph Semantics are now generally available and ready for production use. We encourage all users to integrate this powerful tool into their data analysis workflows. Whether you are looking to enhance your understanding of complex datasets or uncover hidden patterns in your data, the graph semantics extension offers a robust framework for achieving these goals.

How to get started with the graph semantics in Kusto?

Users can learn more about the Graph Semantics by reading our documentation or by playing the Kusto Detective Agency game. Additionally, we recommend to follow our graph samples repository on GitHub which we are using to describe scenarios in depth.

Now, have fun with Graphs in Kusto.

PS: Are you ready for some fun? Launch your Kusto Explorer and pick any database… Do you want to discover the secrets behind the “Show Entities Graph” option?

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