AWS IoT Analytics is a fully-managed service that makes it easy to run and operationalize sophisticated analytics on large volumes of IoT data without managing hardware or infrastructure. It is the easiest way to run analytics on IoT data and get insights to make better and more accurate decisions for IoT applications and machine learning use cases. IoT data is highly unstructured which makes it difficult to analyze with traditional analytics and business intelligence tools that are designed to process structured data. AWS IoT Analytics automates each of the steps that are required to analyze data from IoT devices.
AWS IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can setup the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing the processed data. Then, you can analyze your data by running ad hoc or scheduled queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference.
For more information, visit the AWS IoT Analytics documentation page.
AWS IoT Analytics benefits
Operationalize your analytical workflows
You supply the analysis, while AWS IoT Analytics automates the execution of your analysis when and where you need it. AWS IoT Analytics will import your custom authored code containers (built in external tools such as Matlab, Octave, R, and others), and execute them on your schedule to generate operational insights.
Easily run queries on IoT data
With AWS IoT Analytics, you can run simple, ad-hoc queries using the built-in SQL query engine. For example, using standard SQL queries to extract data from the data store, you can calculate the average distance traveled of a fleet of vehicles or the number of doors locked in a smart building.
Data storage optimized for IoT
AWS IoT Analytics stores the processed device data in a time-series data store that is optimized to deliver fast response times on IoT queries. The raw data is also automatically stored for later processing or reprocessing for another use case.
Prepares your IoT data for analysis
AWS IoT Analytics is integrated with AWS IoT Core to easily ingest device data directly from connected devices, and includes data preparation techniques that make it easy to process your data for analysis. It cleans false readings, fills gaps in the data, and performs mathematical transforms of incoming data. As the data is ingested, AWS IoT Analytics can process it using conditional statements, filter data to collect just the data you want to analyze, and enrich it with information from the AWS IoT Registry or external data sources such as a weather service.
Tools for machine learning
AWS IoT Analytics makes it easy to apply machine learning to your IoT data with hosted Jupyter Notebooks. You can directly connect your IoT data to the notebook and build, train, and execute models right from the AWS IoT Analytics console without having to manage any of the underlying infrastructure. With a single click, you can also package your Jupyter Notebook code into an executable container image and execute it on a schedule.
Automated scaling with pay as you go pricing
AWS IoT Analytics is a fully managed and pay-as-you go service that scales automatically to support up to petabytes of IoT data. With IoT Analytics, you can analyze your entire fleet of connected devices without managing hardware or infrastructure. As your needs change, compute power and the data store automatically scale up or down so you always have the right capacity for your IoT applications and you only pay for the resources that you use.
How it works
Proactive replenishing of supplies
Process efficiency scoring
Mini user guides
AWS IoT Analytics mini user guide: Channels
AWS IoT Analytics mini user guide: Pipelines
AWS IoT Analytics mini user guide: Data stores & data sets
AWS IoT Analytics mini user guide: Analytics & visualization