The Azure Data Factory service provides a general tool for data processing on the Azure platform. However, the second offer which I will introduce to you now, is something more special.

What is Azure Stream Analytics?

Azure Stream Analytics is a real-time data processing tool for streaming data. This means in the cleartext: Azure Stream Analytics takes the data streams, analyzes them in its engine and makes them available to various receivers.

The data streams can come from devices, sensors, websites, social media feeds, applications, and much more. However, it is important to know that the data streams are never tapped directly; the access is always via an Azure IoT Hub and/or an Azure Event Hub.

Let's go to the processing of the data in the engine. This area is script-based and Azure Stream Analytics provides the Stream Analytics query language for this purpose. With the Stream Analytics query language, you can filter and sort the data, aggregate values, perform calculations, join data (within a stream or to reference data), and also use geospatial functions.

Not enough?

You can extend the capabilities by defining and calling additional functions. For example, you can define function calls for the Azure Machine Learning service to take advantage of your Azure Machine Learning solutions. You can also integrate JavaScript user-defined functions (UDFs) to make complex calculations as part of your processing.

In the context of processing, you also have the ability to add historical data or reference data to your process.

The last point refers to the availability of results for different recipients (consumers). In general, the output is always available for several receivers at the same time. So, you can in a single pass, pass data to a data store (for example, Azure Data Lake Store) to provide long-term archiving and simultaneously edit the data in Microsoft PowerBI.