When monitoring surfaces changing data, anomalies, or critical events, alerts are generated or actions are triggered. Real-time data analytics is commonly based on the ingestion and processing of a data stream that consists of a perpetual series of data, typically related to specific point-in-time events. For example, a stream of data from an environmental IoT weather sensor. Real-Time Intelligence in Fabric contains a tool called Activator that can be used to trigger actions on streaming data. For example, a stream of data from an environmental IoT weather sensor might be used to trigger emails to sailors when wind thresholds are met. When certain conditions or logic is met, an action is taken, like alerting users, executing Fabric job items like a pipeline, or kicking off Power Automate workflows. The logic can be either a defined threshold, a pattern like events happening repeatedly over a time period, or the results of logic defined by a Kusto Query Language (KQL) query.
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