Summary

In this chapter, you have learned how to provision an ASA job. You have seen how to connect to sources and sinks and how to use them as inputs and outputs. You have also learned about ASA SQL and its windowing functions.

Furthermore, you have seen that ASA SQL queries can route data from the input to different outputs, creating different granularities. You have examined the capabilities to add reference data to your queries and how to add further functionality such as user-defined functions and machine learning using functions.

Finally, we have talked about SUs, the performance metrics of ASA, and how partitioning will help you to improve performance. You have examined security questions and have learned about monitoring. If all the features of ASA do not deliver on your requirements, there are additional technologies available on Azure, such as Spark clusters in Synapse or Databricks that can be used to implement streaming.

We have touched on the topic of machine...