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One of the key components for effective threat investigation in Azure Sentinel is the use of notebooks. Notebooks allow analysts to create and run Jupyter notebooks that can incorporate live data, enabling them to conduct more detailed and customized data analysis. This interactive format is particularly useful when dealing with large datasets, such as those generated by the monitoring of over 9,000 IoT devices.

By leveraging notebooks, security analysts can document their investigative process, run complex queries across data sources, visualize results, and share insights with other team members. This capability is especially important in identifying and investigating potential threats, as it provides a flexible environment to manipulate data, apply machine learning models, and integrate findings into a broader threat investigation narrative.

The other components serve different purposes that may not be as holistic for an investigation. For instance, bookmarks are better suited for marking specific events or alerts, built-in queries provide useful pre-defined searches but may not address very specific investigation needs, and livestream focuses on real-time event monitoring without the comprehensive analytic capabilities that notebooks provide.