Amazon Kinesis Data Analytics Can Now Detect Hotspots in Real-Time Data Streams

Posted On: Mar 19, 2018

Starting today, Amazon Kinesis Data Analytics supports real-time hotspot detection, which allows you to automatically detect regions of high density in your data, like a high concentration of vehicles on a highway indicating traffic bottlenecks, surging rideshare requests in a certain area indicating a popular event, or higher sales of products within a category indicating feature similarity. Detecting hotspots like these can help you gain actionable insights quickly and react to changing customer and business needs promptly.
To get started, simply call the Kinesis Data Analytics hotspot function from your Kinesis application. The hotspot function automatically builds and trains an appropriate machine learning model to identify subsections of your data streams that need attention. It identifies and reports one or more bounding boxes of these subsections in real-time.

Kinesis Data Analytics hotspot detection is unsupervised, meaning that the function does not require you to label the data for model training. In addition, Kinesis Data Analytics automatically updates the model behind the scenes to adapt to changes in the data stream. For more information including sample code and hotspot visualization, see Detecting Hotspots on a Stream in the Kinesis Data Analytics developer guide.

Kinesis Data Analytics is the easiest way to process data streams in real time with standard SQL without having to learn new programming languages or processing frameworks. Kinesis Data Analytics is available in the US East (N. Virginia), US West (Oregon), and EU (Ireland) regions. To get started, visit the Kinesis Data Analytics management console.