Generate operational insights with tools including MATLAB and Octave when you import and implement custom code containers.
Filter, transform, clean, enrich, and store device data in time-series format for fast retrieval and analysis.
Perform analytics and machine learning (ML) inference with hosted Jupyter notebooks to build and train models without managing infrastructure.
Analyze device performance and visualize trends with a built-in SQL query engine and integration with Amazon QuickSight.
How it works
AWS IoT Analytics simplifies the difficult steps required to analyze massive volumes of IoT data, without the cost and complexity of building an IoT analytics platform.
Enrich IoT data with contextual metadata
Agricultural equipment operators clean and enrich moisture sensor data with predicted rainfall and optimize the water efficiency of irrigation equipment.
Operationalize predictive maintenance
Prebuilt templates help you create powerful predictive maintenance models, such as cargo vehicle models that predict heating and cooling systems’ failure.
Replenish supplies proactively
IoT applications can monitor inventories and analyze data from food vending machines, then accurately reorder merchandise whenever supply runs low.
Improve with process efficiency scoring
Monitor and improve the efficiency of IoT applications, for example, identifying optimum loads for trucks to plan loading guidelines.
How to get started
Start using AWS IoT Analytics
Get access to AWS IoT Analytics and start building today.
Learn how to use AWS IoT Analytics
Check out the user guide and API and CLI reference guides.
Explore key features
Discover how AWS IoT Analytics collects, processes, stores, analyzes, and helps visualize data.