On Thursday, April 21 Microsoft announced the integration between Azure Stream Analytics and Power BI has reached General Availability (GA). Using this capability, customers can gain real-time insight into their business performance by analyzing in-flight data streams.
Azure Stream Analytics is a fully managed Azure service that is capable of performing real-time processing on stream data that is in-motion. In order to use Azure Stream Analytics, developers define inputs, such as Azure Event Hubs, Blob Storage and Azure IoT Hubs (preview). Next, developers define outputs such as Azure Service Bus Topics, Azure Service Bus Queues, Azure Event Hubs, Azure SQL, Azure Document DB, Azure Blob Storage and Power BI. With your inputs and outputs defined you then establish a SQL like query against your inputs which will result in sending a data set to your predefined outputs.
Azure Stream Analytics also provide windowing functionality that allows developers to define queries to execute within a specific timeframe. Data can then be aggregated for the duration of that specific window. Consider an IoT scenario where you have a power meter that is emitting a meter read each second. You may not want to publish the value of that meter read each second as it will generate too much data in downstream systems. Using a window, such as a 15-minute window, will allow a power provider to perform an average calculation on meter read data for that 15-minute window and then publish the aggregated value to downstream systems. Using this approach will significantly reduce the overall size of the dataset that a downstream application needs to consume.
The integration with Power BI was previously in preview and with this functionality, customers can publish their real-time data to Power BI which can render visualizations to be viewed inside a web browser or on a mobile device.
Ryan CrawCour, program manager at Microsoft, describes how customers have historically addressed the need to deliver business insights: “Traditionally, if you wanted to build a system that was able to get 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.”
Crawcour explains why a new model was necessary: “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.”
Using this new capability from Azure Stream Analytics and Power BI, customers can gain real-time insight into the temperature of the fish while in transit. If there was a sudden change in temperature, which could jeopardize the ability to sell that fish, operational information can be pushed to Power BI where performance metrics and real-time dashboards provide immediate insight.