According to Microsoft Sentinel documentation, notebooks integrate with Azure Machine Learning and Jupyter to allow advanced data visualization, enrichment, and correlation with third-party data sources . Notebooks are used by security analysts and threat hunters to perform deep investigations by combining Sentin el data (such as logs, alerts, and incidents) with external threat intelligence feeds, indicators of compromise (IoCs), and custom datasets .
Microsoft describes notebooks as:
“A powerful tool built on Jupyter and Azure Machine Learning that allows you to u se Python code to enrich Microsoft Sentinel data with external data sources, visualize data, and identify patterns and IoCs.”
They allow analysts to query, visualize, and correlate data interactively, going beyond the built-in dashboards and KQL-based anal ytics.
Thus, to visualize Sentinel data and enrich it with third-party IoC data, Notebooks in Azure Sentinel is the correct solution
