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azurepowerbiazure-stream-analytics

How can I decide, if I should use the Power BI API to push data into my streaming dataset or Azure Stream Analytics?


I am very new to Azure. I need to create a Power BI dashboard to visualize some data produced by a sensor. The dashboard needs to get updated "almost" real-time. I have identified that I need a push data set, as I want to visualize some historic data on a line chart. However, from the architecture point of view, I could use the Power BI REST APIs (which would be completely fine in my case, as we process the data with a Python app and I could use that to call Power BI) or Azure Stream Analytics (which could also work, I could dump the data to the Azure Blob storage from the Python app and then stream it). Can you tell me generally speaking, what are the advantages/disadvantages of the two approaches?


Solution

  • Azure stream analytics lets you have multiple sources and define multiple targets and one of those targets could be Power-BI and Blob ... and at the same time you can use windowing function on the data as it comes in. It also provides you a visual way of managing your pipeline including windowing function.

    In your case you are kind of replicating the incoming data to Blob first and secondly to power-BI. But if you have a use case to apply windowing function(1 minutes or so) as your data is coming in from multiple sources e.g. more than one sensor or a senor and other source, you have to fiddle around a lot to get it working manually, where as in stream analytics you can easily do it.

    Following article highlights some of the pros and cons of Azure Analytics... https://www.axonize.com/blog/iot-technology/the-advantages-and-disadvantages-of-using-azure-stream-analytics-for-iot-applications/