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.
Specifies one or more sets of channel messages.
Statistics information about the channel.
Where channel data is stored. You may choose one of
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.
Contains information about a column that stores your data.
Information required to run the
containerAction to produce dataset 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. You cannot change the choice of service-managed or customer-managed S3 storage after the channel is created.
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. You cannot change the choice of service-managed or customer-managed S3 storage after the data store is created.
Used to store data store data in an S3 bucket that you manage.
Information about a data set.
DatasetAction object that specifies how data set contents are automatically created.
Information about the action that automatically creates the dataset's contents.
The destination to which dataset contents are delivered.
When dataset 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 dataset contents.
The dataset 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.
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.
A single partition in a data store.
Contains information about partitions in a data store.
Statistical information about the data store.
Where data store data is stored. You can choose one of
customerManagedS3 storage. If not specified, the default is
serviceManagedS3. You cannot change this storage option 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.
A structure that contains the configuration information of a delta time session window.
DeltaTime specifies a time interval. You can use
DeltaTime to create dataset contents with data that has arrived in the data store since the last execution. For an example of
DeltaTime, see Creating a SQL dataset with a delta window (CLI) in the AWS IoT Analytics User Guide.
An activity that adds data from the AWS IoT device registry to your message.
An activity that adds information from the AWS IoT Device Shadow service to a message.
The estimated size of the resource.
Contains the configuration information of file formats. AWS IoT Analytics data stores support JSON and Parquet.
The default file format is JSON. You can specify only one format.
You can't change the file format after you create the data store.
An activity that filters a message based on its attributes.
Configuration information for coordination with AWS Glue, a fully managed extract, transform and load (ETL) service.
A client for the AWS IoT Analytics API.
Configuration information for delivery of dataset contents to AWS IoT Events.
Contains the configuration information of the JSON format.
An activity that runs a Lambda function to modify the message.
A structure that contains the name and configuration information of a late data rule.
The information needed to configure a delta time session window.
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 the configuration information of the Parquet format.
A single partition.
Contains information about a pipeline.
An activity that performs a transformation on a message.
A summary of information about a pipeline.
Information that is used to filter message data, to segregate it according to the timeframe 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
How long, in days, message data is kept.
Configuration information for delivery of dataset contents to Amazon Simple Storage Service (Amazon S3).
The schedule for when to trigger an update.
Information needed to define a schema.
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 AWS IoT Analytics. You cannot change the choice of service-managed or customer-managed S3 storage after the channel is created.
Used to store channel data in an S3 bucket managed by AWS IoT Analytics.
Use this to store data store data in an S3 bucket managed by AWS IoT Analytics. You cannot change the choice of service-managed or customer-managed S3 storage after the data store is created.
Used to store data store data in an S3 bucket managed by AWS IoT Analytics.
The SQL query to modify the message.
A set of key-value pairs that are used to manage the resource.
A partition defined by a timestamp.
Information about the dataset whose content generation triggers the new dataset 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
Information about the versioning of dataset 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.