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AWS IoT Analytics

AWS IoT Analytics

Fully managed, operationalized analytics for your IoT devices

End of Support Notice

 On December 15, 2025, AWS will discontinue support for AWS IoT Analytics. After December 15, 2025, you will no longer be able to access AWS IoT Analytics console or resources. For more information, see guide.

Benefits

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 AWS IoT Analytics worksHow AWS IoT Analytics works

IoT data comes from devices that record noisy processes (such as temperature, motion, or sound). This data can have significant gaps, corrupted messages, or false readings, which need to be cleaned before analysis.IoT data comes from devices that record noisy processes (such as temperature, motion, or sound). This data can have significant gaps, corrupted messages, or false readings, which need to be cleaned before analysis.

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.

Use cases

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.