AWS IoT Analytics allows you to collect large amounts of device data, process messages, and store them. You can then query the data and run sophisticated analytics on it. AWS IoT Analytics enables advanced data exploration through integration with Jupyter Notebooks and data visualization through integration with Amazon QuickSight.
Traditional analytics and business intelligence tools are designed to process structured data. IoT data often comes from devices that record noisy processes (such as temperature, motion, or sound). As a result the data from these devices can have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of other data from external sources.
AWS IoT Analytics automates the steps 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 set up 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 it. Then, you can analyze your data by running queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. AWS IoT Analytics includes pre-built models for common IoT use cases so you can answer questions like which devices are about to fail or which customers are at risk of abandoning their wearable devices.
An activity that adds other attributes based on existing attributes in the message.
Contains informations about errors.
A collection of data from an MQTT topic. Channels archive the raw, unprocessed messages before publishing the data to a pipeline.
The activity that determines the source of the messages to be processed.
Statistics information about the channel.
Where channel data is stored. You may choose one of "serviceManagedS3" or "customerManagedS3" storage. If not specified, the default is "serviceManagedS3". This cannot be changed after creation of the channel.
Where channel data is stored.
A summary of information about a channel.
Information needed to run the "containerAction" to produce data set contents.
Use this to store channel data in an S3 bucket that you manage. If customer managed storage is selected, the "retentionPeriod" parameter is ignored. The choice of service-managed or customer-managed S3 storage cannot be changed after creation of the channel.
Used to store channel data in an S3 bucket that you manage.
Use this to store data store data in an S3 bucket that you manage. When customer managed storage is selected, the "retentionPeriod" parameter is ignored. The choice of service-managed or customer-managed S3 storage cannot be changed after creation of the data store.
Used to store data store data in an S3 bucket that you manage.
Information about a data set.
A "DatasetAction" object that specifies how data set contents are automatically created.
Information about the action which automatically creates the data set's contents.
The destination to which data set contents are delivered.
When data set contents are created they are delivered to destination specified here.
The state of the data set contents and the reason they are in this state.
Summary information about data set contents.
The data set whose latest contents are used as input to the notebook or application.
The reference to a data set entry.
A summary of information about a data set.
The "DatasetTrigger" that specifies when the data set is automatically updated.
Information about a data store.
The 'datastore' activity that specifies where to store the processed data.
Statistical information about the data store.
Where data store data is stored. You may choose one of "serviceManagedS3" or "customerManagedS3" storage. If not specified, the default is "serviceManagedS3". This cannot be changed after the data store is created.
Where data store data is stored.
A summary of information about a data store.
Used to limit data to that which has arrived since the last execution of the action.
An activity that adds data from the AWS IoT device registry to your message.
An activity that adds information from the AWS IoT Device Shadows service to a message.
The estimated size of the resource.
An activity that filters a message based on its attributes.
Configuration information for coordination with the AWS Glue ETL (extract, transform and load) service.
A client for the AWS IoT Analytics API.
Configuration information for delivery of data set contents to AWS IoT Events.
An activity that runs a Lambda function to modify the message.
Information about logging options.
An activity that computes an arithmetic expression using the message's attributes.
Information about a message.
The value of the variable as a structure that specifies an output file URI.
Contains information about a pipeline.
An activity that performs a transformation on a message.
A summary of information about a pipeline.
Information which is used to filter message data, to segregate it according to the time frame in which it arrives.
An activity that removes attributes from a message.
Information about pipeline reprocessing.
The configuration of the resource used to execute the "containerAction".
How long, in days, message data is kept.
Configuration information for delivery of data set contents to Amazon S3.
The schedule for when to trigger an update.
Creates a new message using only the specified attributes from the original message.
Use this to store channel data in an S3 bucket managed by the AWS IoT Analytics service. The choice of service-managed or customer-managed S3 storage cannot be changed after creation of the channel.
Used to store channel data in an S3 bucket managed by the AWS IoT Analytics service.
Use this to store data store data in an S3 bucket managed by the AWS IoT Analytics service. The choice of service-managed or customer-managed S3 storage cannot be changed after creation of the data store.
Used to store data store data in an S3 bucket managed by the AWS IoT Analytics service.
The SQL query to modify the message.
A set of key/value pairs which are used to manage the resource.
Information about the data set whose content generation triggers the new data set content generation.
An instance of a variable to be passed to the "containerAction" execution. Each variable must have a name and a value given by one of "stringValue", "datasetContentVersionValue", or "outputFileUriValue".
Information about the versioning of data set contents.
Errors returned by BatchPutMessage
Errors returned by CancelPipelineReprocessing
Errors returned by CreateChannel
Errors returned by CreateDatasetContent
Errors returned by CreateDataset
Errors returned by CreateDatastore
Errors returned by CreatePipeline
Errors returned by DeleteChannel
Errors returned by DeleteDatasetContent
Errors returned by DeleteDataset
Errors returned by DeleteDatastore
Errors returned by DeletePipeline
Errors returned by DescribeChannel
Errors returned by DescribeDataset
Errors returned by DescribeDatastore
Errors returned by DescribeLoggingOptions
Errors returned by DescribePipeline
Errors returned by GetDatasetContent
Errors returned by ListChannels
Errors returned by ListDatasetContents
Errors returned by ListDatasets
Errors returned by ListDatastores
Errors returned by ListPipelines
Errors returned by ListTagsForResource
Errors returned by PutLoggingOptions
Errors returned by RunPipelineActivity
Errors returned by SampleChannelData
Errors returned by StartPipelineReprocessing
Errors returned by TagResource
Errors returned by UntagResource
Errors returned by UpdateChannel
Errors returned by UpdateDataset
Errors returned by UpdateDatastore
Errors returned by UpdatePipeline
Trait representing the capabilities of the AWS IoT Analytics API. AWS IoT Analytics clients implement this trait.