Today we are pleased to announce the general availability of the integration between Azure Stream Analytics and Power BI. With this capability you are able to create interactive real-time dashboards for streaming data from devices, sensors, infrastructure and even your business applications.
The power of real-time dashboards
Data is everywhere. It is coming at us from an ever increasing number of sources at a higher velocity every day and we’re under more and more pressure to turn this data into business insights and shorten our time to react.
Imagine, for example, you managed a fleet of refrigerated trucks that carry fresh fish from the docks to markets all over the country and the air conditioning unit in one of these trucks malfunctioned and your fish began to heat up, I suspect you’d want to know about this and be able to take action on this in the shortest time possible.
Traditionally, if you wanted to build a system that was able to get you this sort of insight from your data and display this on a dashboard you would have to first ingest the data, process the data, store the data in a database somewhere and then write a custom application to continually poll this database and populate a customer dashboard you had to build yourself. Sure, it’s possible to do but when we’re dealing with a truck load of fish that is about to spoil, you want this info within seconds, not minutes and without having to deal with the complexity involved.
Real-time dashboards provide a live view of the metrics that matter most to your business allowing for faster time to insight and action.
From monitoring the temperature inside a refrigerated truck to facilitating sales and marketing teams by tracking hourly performance metrics, real-time dashboards deliver business value in a growing number of real-world scenarios.
Why Stream Analytics?
Azure Stream Analytics is a fully managed, cost effective Azure Service that enables you to do real-time stream processing on data in-motion using a simple SQL like language. Stream Analytics provides a number of input connectors, such as Azure Event Hubs and Azure IoT Hubs, which allow you to easily ingest data at scale. Using a Stream Analytics job you can then do aggregations, filtering, and grouping of the streaming data on temporal windows. You can then connect a number of downstream databases and systems, such as SQL DB and DocumentDB to persist the results of your analytic computations.
With today’s announcement we are adding another output connector, the Power BI connector, which allows you to stream data directly to a live dashboard. This will dramatically reduce the latency and time to action on your most important business metrics. We have been working with hundreds of customers in public preview to visualize data from sensors, business applications, social media, user logs etc. This integration is now available to all customers.
The video below shows an example of what can be done through the power of streaming data to real-time dashboards.
Getting started
If you would like to learn how to do this yourself, you can refer to the Stream Analytics & Power BI tutorial. Here you will learn how create your own custom business intelligence tools using Power BI as an output for your Azure Stream Analytics jobs.
Next steps
We’re really excited about this integration and hope it will unlock many new exciting capabilities for you and your real-time dashboards. We welcome you to provide feedback on what you want to see next on our User Voice page!
If you are new to either Microsoft Azure or Stream Analytics, try it out by signing up for a free Azure trial account and create your first Stream Analytics job.
If you need help or have questions, please reach out to us through the MSDN or Stackoverflow forums or to the product team directly by email.
Stay up-to-date on the latest news and features by following us on Twitter @AzureStreaming.
