Imagine that your organization has smart devices in various locations. To gain insights from the data generated by those devices, you need to send all the data to a central application for further analysis.
By adding centralized, real-time analysis to the data, you can gain more value from these devices and act on the insights in real time. In addition, you can detect potential problems before they occur. For example, if any of the devices is reporting data that is unusual when compared to the general average, your application can detect this and create an alert.
This video shows a Streams application that analyzes data from sensors and checks for outliers. The application is running in a Python notebook in IBM Watson Studio and the results of the analysis are visualized right in the notebook.
The application analyzes data generated by an Apache Edgent application. This demonstrates how you could use Streams to add centralized analytics to the data from IoT devices.
Note: This video refers to Watson Data Platform and Data Science Experience, both of which are now part of Watson Studio.