Stream processing involves several key components, including data ingestion, data processing, and data output. Data is ingested from the stream source, processed using algorithms, filters, aggregations, or other operations, and then delivered to one or more destinations, such as databases, dashboards, or other applications.

Streaming data processing facilitates the quick identification of critical events or anomalies. By continuously analyzing incoming data in real-time, organizations can promptly detect and respond to issues, such as fraud, security breaches, system failures, or any other events that require immediate attention. This proactive approach can help mitigate risks and minimize the impact of potential problems.

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