In this chapter, you learned about enhancing Stream Analytics real-time event processing queries, optimized through integrating with JavaScript functions for data transformation, mathematical or statistical analysis purposes, and applying intelligent predictive algorithms using Azure machine learning web services with interactive data streams. Finally, step-by-step implementation guidance was analyzed to build a Stream Analytics job with customized input, output, and job transformation, and starting and stopping phases using the .NET REST API.
In the next chapter, we will focus on understanding the Stream Analytics job monitoring and management processes using job diagram metrics, resource health enhancement, diagnostics log collection for troubleshooting, and architectural principles of designing optimized job monitoring concepts.
