Analytics - IoT Lens


The primary business case for implementing IoT solutions is to respond more quickly to how devices are performing and being used in the field. By acting directly on incoming telemetry, businesses can make more informed decisions about which new products or features to prioritize, or how to more efficiently operate workflows within their organization. Analytics services must be selected in such a way that gives you varying views on your data based on the type of analysis you are performing. AWS provides several services that align with different analytics workflows including time-series analytics, real-time metrics, and archival and data lake use cases.

With IoT data, your application can generate time-series analytics on top of the steaming data messages. You can calculate metrics over time windows and then stream values to other AWS services.

In addition, IoT applications that use AWS IoT Analytics can implement a managed AWS Data Pipeline consisting of data transformation, enrichment, and filtering before storing data in a time series data store. Additionally, with AWS IoT Analytics, visualizations and analytics can be performed natively using QuickSight and Jupyter Notebooks.