Graphs are a powerful way to model and analyse complex relationships between entities, such as cybersecurity incidents, network traffic, social networks, and more. Kusto, the query and analytics engine of Azure Data Explorer, Microsoft Fabric Real-Time Analytics and many more recently introduced a new feature that enables users to contextualize their data using graphs. In this blog post, we will show you how to use graph semantics to create and explore graph data in Kusto, and how to visualize it using Plotly, a popular library for interactive data visualization in Python.
Graph semantics are a set of operators that allow users to work with graph data in Kusto, without the need to use a separate graph database or framework.
Click through for the KQL you’ll need, as well as how to display that in Plotly.