A JSON description of the data that is in each time series dataset, including names, column names, and data types.

Provides the identifier of the KMS key used to encrypt dataset data by Amazon Lookout for Equipment.

Any tags associated with the ingested data described in the dataset.

The name of the dataset being created.

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

The Amazon Resource Name (ARN) of the dataset being created.

The name of the dataset being created.

Indicates the status of the CreateDataset operation.

The response's http status code.

The interval (in minutes) of planned delay at the start of each inference segment. For example, if inference is set to run every ten minutes, the delay is set to five minutes and the time is 09:08. The inference scheduler will wake up at the configured interval (which, without a delay configured, would be 09:10) plus the additional five minute delay time (so 09:15) to check your Amazon S3 bucket. The delay provides a buffer for you to upload data at the same frequency, so that you don't have to stop and restart the scheduler when uploading new data.

For more information, see Understanding the inference process.

Provides the identifier of the KMS key used to encrypt inference scheduler data by Amazon Lookout for Equipment.

Any tags associated with the inference scheduler.

The name of the previously trained ML model being used to create the inference scheduler.

The name of the inference scheduler being created.

How often data is uploaded to the source Amazon S3 bucket for the input data. The value chosen is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment runs inference on your data.

For more information, see Understanding the inference process.

Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

Specifies configuration information for the output results for the inference scheduler, including the S3 location for the output.

The Amazon Resource Name (ARN) of a role with permission to access the data source being used for the inference.

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

The Amazon Resource Name (ARN) of the inference scheduler being created.

The name of inference scheduler being created.

Indicates the status of the CreateInferenceScheduler operation.

The response's http status code.

Indicates that a label pertains to a particular piece of equipment.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

Provides additional information about the label. The fault code must be defined in the FaultCodes attribute of the label group.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

Metadata providing additional information about the label.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

The name of a group of labels.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

The start time of the labeled event.

The end time of the labeled event.

Indicates whether a labeled event represents an anomaly.

A unique identifier for the request to create a label. If you do not set the client request token, Lookout for Equipment generates one.

The ID of the label that you have created.

The response's http status code.

The acceptable fault codes (indicating the type of anomaly associated with the label) that can be used with this label group.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

Tags that provide metadata about the label group you are creating.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

Names a group of labels.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

A unique identifier for the request to create a label group. If you do not set the client request token, Lookout for Equipment generates one.

The ARN of the label group that you have created.

The name of the label group that you have created. Data in this field will be retained for service usage. Follow best practices for the security of your data.

The response's http status code.

The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.

When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H

The data schema for the ML model being created.

Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the ML model.

Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the ML model.

The input configuration for the labels being used for the ML model that's being created.

Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.

The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the ML model.

Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.

Any tags associated with the ML model being created.

Indicates the time reference in the dataset that should be used to end the subset of training data for the ML model.

Indicates the time reference in the dataset that should be used to begin the subset of training data for the ML model.

The name for the ML model to be created.

The name of the dataset for the ML model being created.

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

The Amazon Resource Name (ARN) of the model being created.

Indicates the status of the CreateModel operation.

The response's http status code.

The name of the dataset to be deleted.

The name of the inference scheduler to be deleted.

The name of the label group that contains the label that you want to delete. Data in this field will be retained for service usage. Follow best practices for the security of your data.

The ID of the label that you want to delete.

The name of the label group that you want to delete. Data in this field will be retained for service usage. Follow best practices for the security of your data.

The name of the ML model to be deleted.

The job ID of the data ingestion job.

The time at which the data ingestion job was created.

Indicates the latest timestamp corresponding to data that was successfully ingested during this specific ingestion job.

Gives statistics about a completed ingestion job. These statistics primarily relate to quantifying incorrect data such as MissingCompleteSensorData, MissingSensorData, UnsupportedDateFormats, InsufficientSensorData, and DuplicateTimeStamps.

Indicates the earliest timestamp corresponding to data that was successfully ingested during this specific ingestion job.

The Amazon Resource Name (ARN) of the dataset being used in the data ingestion job.

Specifies the reason for failure when a data ingestion job has failed.

Indicates the size of the ingested dataset.

Undocumented member.

Specifies the S3 location configuration for the data input for the data ingestion job.

Indicates the job ID of the data ingestion job.

The Amazon Resource Name (ARN) of an IAM role with permission to access the data source being ingested.

Indicates the status of the DataIngestionJob operation.

Provides details about status of the ingestion job that is currently in progress.

The response's http status code.

The name of the dataset to be described.

Specifies the time the dataset was created in Lookout for Equipment.

Indicates the latest timestamp corresponding to data that was successfully ingested during the most recent ingestion of this particular dataset.

Gives statistics associated with the given dataset for the latest successful associated ingestion job id. These statistics primarily relate to quantifying incorrect data such as MissingCompleteSensorData, MissingSensorData, UnsupportedDateFormats, InsufficientSensorData, and DuplicateTimeStamps.

Indicates the earliest timestamp corresponding to data that was successfully ingested during the most recent ingestion of this particular dataset.

The Amazon Resource Name (ARN) of the dataset being described.

The name of the dataset being described.

IngestedFilesSummary associated with the given dataset for the latest successful associated ingestion job id.

Specifies the S3 location configuration for the data input for the data ingestion job.

Specifies the time the dataset was last updated, if it was.

The Amazon Resource Name (ARN) of the IAM role that you are using for this the data ingestion job.

A JSON description of the data that is in each time series dataset, including names, column names, and data types.

Provides the identifier of the KMS key used to encrypt dataset data by Amazon Lookout for Equipment.

Indicates the status of the dataset.

The response's http status code.

The name of the inference scheduler being described.

Specifies the time at which the inference scheduler was created.

A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if you select an offset delay time of five minutes, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don't need to stop and restart the scheduler when uploading new data.

Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

Specifies information for the output results for the inference scheduler, including the output S3 location.

Specifies how often data is uploaded to the source S3 bucket for the input data. This value is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes.

The Amazon Resource Name (ARN) of the inference scheduler being described.

The name of the inference scheduler being described.

Indicates whether the latest execution for the inference scheduler was Anomalous (anomalous events found) or Normal (no anomalous events found).

The Amazon Resource Name (ARN) of the ML model of the inference scheduler being described.

The name of the ML model of the inference scheduler being described.

The Amazon Resource Name (ARN) of a role with permission to access the data source for the inference scheduler being described.

Provides the identifier of the KMS key used to encrypt inference scheduler data by Amazon Lookout for Equipment.

Indicates the status of the inference scheduler.

Specifies the time at which the inference scheduler was last updated, if it was.

The response's http status code.

Returns the name of the group containing the label.

Returns the ID of the label.

The time at which the label was created.

The end time of the requested label.

Indicates that a label pertains to a particular piece of equipment.

Indicates the type of anomaly associated with the label.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

The ARN of the requested label group.

The name of the requested label group.

The ID of the requested label.

Metadata providing additional information about the label.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

Indicates whether a labeled event represents an anomaly.

The start time of the requested label.

The response's http status code.

Returns the name of the label group.

The time at which the label group was created.

Codes indicating the type of anomaly associated with the labels in the lagbel group.

The ARN of the label group.

The name of the label group.

The time at which the label group was updated.

The response's http status code.

The name of the ML model to be described.

Indicates the time and date at which the ML model was created.

The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.

When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H

The Amazon Resouce Name (ARN) of the dataset used to create the ML model being described.

The name of the dataset being used by the ML being described.

Indicates the time reference in the dataset that was used to end the subset of evaluation data for the ML model.

Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the ML model.

If the training of the ML model failed, this indicates the reason for that failure.

Specifies configuration information about the labels input, including its S3 location.

Indicates the last time the ML model was updated. The type of update is not specified.

The Amazon Resource Name (ARN) of the ML model being described.

The Model Metrics show an aggregated summary of the model's performance within the evaluation time range. This is the JSON content of the metrics created when evaluating the model.

The name of the ML model being described.

Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.

The Amazon Resource Name (ARN) of a role with permission to access the data source for the ML model being described.

A JSON description of the data that is in each time series dataset, including names, column names, and data types.

Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.

Specifies the current status of the model being described. Status describes the status of the most recent action of the model.

Indicates the time reference in the dataset that was used to end the subset of training data for the ML model.

Indicates the time reference in the dataset that was used to begin the subset of training data for the ML model.

Indicates the time at which the training of the ML model was completed.

Indicates the time at which the training of the ML model began.

The response's http status code.

The name of the dataset being used for the data ingestion job.

Specifies the maximum number of data ingestion jobs to list.

An opaque pagination token indicating where to continue the listing of data ingestion jobs.

Indicates the status of the data ingestion job.

Specifies information about the specific data ingestion job, including dataset name and status.

An opaque pagination token indicating where to continue the listing of data ingestion jobs.

The response's http status code.

The beginning of the name of the datasets to be listed.

Specifies the maximum number of datasets to list.

An opaque pagination token indicating where to continue the listing of datasets.

Provides information about the specified dataset, including creation time, dataset ARN, and status.

An opaque pagination token indicating where to continue the listing of datasets.

The response's http status code.

Specifies the maximum number of inference events to list.

An opaque pagination token indicating where to continue the listing of inference events.

The name of the inference scheduler for the inference events listed.

Lookout for Equipment will return all the inference events with an end time equal to or greater than the start time given.

Returns all the inference events with an end start time equal to or greater than less than the end time given

Provides an array of information about the individual inference events returned from the ListInferenceEvents operation, including scheduler used, event start time, event end time, diagnostics, and so on.

An opaque pagination token indicating where to continue the listing of inference executions.

The response's http status code.

The time reference in the inferenced dataset before which Amazon Lookout for Equipment stopped the inference execution.

The time reference in the inferenced dataset after which Amazon Lookout for Equipment started the inference execution.

Specifies the maximum number of inference executions to list.

An opaque pagination token indicating where to continue the listing of inference executions.

The status of the inference execution.

The name of the inference scheduler for the inference execution listed.

Provides an array of information about the individual inference executions returned from the ListInferenceExecutions operation, including model used, inference scheduler, data configuration, and so on.

An opaque pagination token indicating where to continue the listing of inference executions.

The response's http status code.

The beginning of the name of the inference schedulers to be listed.

Specifies the maximum number of inference schedulers to list.

The name of the ML model used by the inference scheduler to be listed.

An opaque pagination token indicating where to continue the listing of inference schedulers.

Specifies the current status of the inference schedulers to list.

Provides information about the specified inference scheduler, including data upload frequency, model name and ARN, and status.

An opaque pagination token indicating where to continue the listing of inference schedulers.

The response's http status code.

The beginning of the name of the label groups to be listed.

Specifies the maximum number of label groups to list.

An opaque pagination token indicating where to continue the listing of label groups.

A summary of the label groups.

An opaque pagination token indicating where to continue the listing of label groups.

The response's http status code.

Lists the labels that pertain to a particular piece of equipment.

Returns labels with a particular fault code.

Returns all labels with a start time earlier than the end time given.

Returns all the labels with a end time equal to or later than the start time given.

Specifies the maximum number of labels to list.

An opaque pagination token indicating where to continue the listing of label groups.

Retruns the name of the label group.

A summary of the items in the label group.

An opaque pagination token indicating where to continue the listing of datasets.

The response's http status code.

The beginning of the name of the dataset of the ML models to be listed.

Specifies the maximum number of ML models to list.

The beginning of the name of the ML models being listed.

An opaque pagination token indicating where to continue the listing of ML models.

The status of the ML model.

Provides information on the specified model, including created time, model and dataset ARNs, and status.

An opaque pagination token indicating where to continue the listing of ML models.

The response's http status code.

The ingestion job id associated with the list of Sensor Statistics. To get sensor statistics for a particular ingestion job id, both dataset name and ingestion job id must be submitted as inputs.

Specifies the maximum number of sensors for which to retrieve statistics.

An opaque pagination token indicating where to continue the listing of sensor statistics.

The name of the dataset associated with the list of Sensor Statistics.

An opaque pagination token indicating where to continue the listing of sensor statistics.

Provides ingestion-based statistics regarding the specified sensor with respect to various validation types, such as whether data exists, the number and percentage of missing values, and the number and percentage of duplicate timestamps.

The response's http status code.

The Amazon Resource Name (ARN) of the resource (such as the dataset or model) that is the focus of the ListTagsForResource operation.

Any tags associated with the resource.

The response's http status code.

The name of the dataset being used by the data ingestion job.

Specifies information for the input data for the data ingestion job, including dataset S3 location.

The Amazon Resource Name (ARN) of a role with permission to access the data source for the data ingestion job.

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

Indicates the job ID of the data ingestion job.

Indicates the status of the StartDataIngestionJob operation.

The response's http status code.

The name of the inference scheduler to be started.

The Amazon Resource Name (ARN) of the inference scheduler being started.

The name of the inference scheduler being started.

The Amazon Resource Name (ARN) of the ML model being used by the inference scheduler.

The name of the ML model being used by the inference scheduler.

Indicates the status of the inference scheduler.

The response's http status code.

The name of the inference scheduler to be stopped.

The Amazon Resource Name (ARN) of the inference schedule being stopped.

The name of the inference scheduler being stopped.

The Amazon Resource Name (ARN) of the ML model used by the inference scheduler being stopped.

The name of the ML model used by the inference scheduler being stopped.

Indicates the status of the inference scheduler.

The response's http status code.

The Amazon Resource Name (ARN) of the specific resource to which the tag should be associated.

The tag or tags to be associated with a specific resource. Both the tag key and value are specified.

The response's http status code.

The Amazon Resource Name (ARN) of the resource to which the tag is currently associated.

Specifies the key of the tag to be removed from a specified resource.

The response's http status code.

A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if you select an offset delay time of five minutes, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don't need to stop and restart the scheduler when uploading new data.

Specifies information for the input data for the inference scheduler, including delimiter, format, and dataset location.

Specifies information for the output results from the inference scheduler, including the output S3 location.

How often data is uploaded to the source S3 bucket for the input data. The value chosen is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes.

The Amazon Resource Name (ARN) of a role with permission to access the data source for the inference scheduler.

The name of the inference scheduler to be updated.

Updates the code indicating the type of anomaly associated with the label.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

The name of the label group to be updated.

Indicates the number of categories in the data.

Indicates whether there is a potential data issue related to categorical values.

Indicates the count of occurences of the given statistic.

Indicates the percentage of occurances of the given statistic.

The Amazon Resource Name (ARN) of the dataset used in the data ingestion job.

The name of the dataset used for the data ingestion job.

Specifies information for the input data for the data inference job, including data Amazon S3 location parameters.

Indicates the job ID of the data ingestion job.

Indicates the status of the data ingestion job.

The sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.

When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H

Parameter that gives information about insufficient data for sensors in the dataset. This includes information about those sensors that have complete data missing and those with a short date range.

Parameter that gives information about data that is missing over all the sensors in the input data.

Parameter that gives information about data that is invalid over all the sensors in the input data.

Parameter that gives information about unsupported timestamps in the input data.

Parameter that gives information about duplicate timestamps in the input data.

The time at which the dataset was created in Amazon Lookout for Equipment.

The Amazon Resource Name (ARN) of the specified dataset.

The name of the dataset.

Indicates the status of the dataset.

Indicates the total number of duplicate timestamps.

An array which specifies the names and values of all sensors contributing to an inference event.

Indicates the size of an inference event in seconds.

Indicates the ending time of an inference event.

Indicates the starting time of an inference event.

The Amazon Resource Name (ARN) of the inference scheduler being used for the inference event.

The name of the inference scheduler being used for the inference events.

Indicates the time reference in the dataset at which the inference execution stopped.

Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

Specifies configuration information for the output results from for the inference execution, including the output Amazon S3 location.

Indicates the time reference in the dataset at which the inference execution began.

Specifies the reason for failure when an inference execution has failed.

The Amazon Resource Name (ARN) of the inference scheduler being used for the inference execution.

The name of the inference scheduler being used for the inference execution.

The Amazon Resource Name (ARN) of the ML model used for the inference execution.

The name of the ML model being used for the inference execution.

Indicates the start time at which the inference scheduler began the specific inference execution.

Indicates the status of the inference execution.

Specifies configuration information for the input data for the inference, including timestamp format and delimiter.

Indicates the difference between your time zone and Coordinated Universal Time (UTC).

Specifies configuration information for the input data for the inference, including Amazon S3 location of input data.

Indicates the delimiter character used between items in the data.

The format of the timestamp, whether Epoch time, or standard, with or without hyphens (-).

The ID number for the AWS KMS key used to encrypt the inference output.

Specifies configuration information for the output results from for the inference, output S3 location.

The prefix for the S3 bucket used for the input data for the inference.

The bucket containing the input dataset for the inference.

The prefix for the S3 bucket used for the output results from the inference.

The bucket containing the output results from the inference

A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if an offset delay time of five minutes was selected, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don't need to stop and restart the scheduler when uploading new data.

How often data is uploaded to the source S3 bucket for the input data. This value is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes.

The Amazon Resource Name (ARN) of the inference scheduler.

The name of the inference scheduler.

Indicates whether the latest execution for the inference scheduler was Anomalous (anomalous events found) or Normal (no anomalous events found).

The Amazon Resource Name (ARN) of the ML model used by the inference scheduler.

The name of the ML model used for the inference scheduler.

Indicates the status of the inference scheduler.

Indicates the number of files that were discarded. A file could be discarded because its format is invalid (for example, a jpg or pdf) or not readable.

Indicates the total number of files that were submitted for ingestion.

Indicates the number of files that were successfully ingested.

The location information for the S3 bucket used for input data for the data ingestion.

Pattern for matching the Amazon S3 files which will be used for ingestion. If no KeyPattern is provided, we will use the default hierarchy file structure, which is same as KeyPattern {prefix}/{component_name}/*

The prefix for the S3 location being used for the input data for the data ingestion.

The name of the S3 bucket used for the input data for the data ingestion.

Parameter that describes the total number of sensors that have data completely missing for it.

Parameter that describes the total number of sensors that have a short date range of less than 90 days of data overall.

Indicates the number of sensors that have at least some invalid values.

Indicates the total number of invalid values across all the sensors.

The time at which the label group was created.

The ARN of the label group.

The name of the label group.

The time at which the label group was updated.

The time at which the label was created.

The timestamp indicating the end of the label.

Indicates that a label pertains to a particular piece of equipment.

Indicates the type of anomaly associated with the label.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

The ARN of the label group.

The name of the label group.

The ID of the label.

Indicates whether a labeled event represents an anomaly.

The timestamp indicating the start of the label.

The name of the label group to be used for label data.

Contains location information for the S3 location being used for label data.

The prefix for the S3 bucket used for the label data.

The name of the S3 bucket holding the label data.

Indicates the size of the largest timestamp gap, in days.

Indicates the number of large timestamp gaps, if there are any.

Indicates whether there is a potential data issue related to large gaps in timestamps.

Indicates the number of sensors that have data missing completely.

Indicates the number of sensors that have atleast some data missing.

Indicates the total number of missing values across all the sensors.

The time at which the specific model was created.

The Amazon Resource Name (ARN) of the dataset used to create the model.

The name of the dataset being used for the ML model.

The Amazon Resource Name (ARN) of the ML model.

The name of the ML model.

Indicates the status of the ML model.

Indicates the monotonicity of values. Can be INCREASING, DECREASING, or STATIC.

Indicates whether there is a potential data issue related to having monotonic values.

Indicates whether there is a potential data issue related to having multiple operating modes.

The name of the specific S3 bucket.

The AWS Key Management Service (AWS KMS) key being used to encrypt the S3 object. Without this key, data in the bucket is not accessible.

Parameter that describes potential risk about whether data associated with the sensor is categorical.

Name of the component to which the particular sensor belongs for which the statistics belong to.

Indicates the time reference to indicate the end of valid data associated with the sensor that the statistics belong to.

Parameter that indicates whether data exists for the sensor that the statistics belong to.

Indicates the time reference to indicate the beginning of valid data associated with the sensor that the statistics belong to.

Parameter that describes the total number of duplicate timestamp records associated with the sensor that the statistics belong to.

Parameter that describes the total number of invalid date entries associated with the sensor that the statistics belong to.

Parameter that describes the total number of, and percentage of, values that are invalid for the sensor that the statistics belong to.

Parameter that describes potential risk about whether data associated with the sensor contains one or more large gaps between consecutive timestamps.

Parameter that describes the total number of, and percentage of, values that are missing for the sensor that the statistics belong to.

Parameter that describes potential risk about whether data associated with the sensor is mostly monotonic.

Parameter that describes potential risk about whether data associated with the sensor has more than one operating mode.

Name of the sensor that the statistics belong to.

Indicates the number of sensors that have less than 90 days of data.

The key for the specified tag.

The value for the specified tag.

Indicates the total number of unsupported timestamps across the ingested data.