Configuring Metric Quality Rule and Analysis Templates¶

Before analyzing data quality for specific metrics, make sure that application creators have configured the following templates:

Quality rule configuration: This template specifies the rules of data quality assessment for each metric. The template contains information including metric identifiers, asset granularity and asset types applicable to the rules, rule templates, and specific rule configurations.
Quality analysis configuration: This template specifies the models and measurement points associated to the specified metrics. The template can be used to perform root cause analysis on data quality issues of the specified metrics.

Quality Rule Configuration¶

Quality rule configuration is used to specify the rules of data quality assessment, to calculate the completeness and validity of the metric. Download, configure, and upload quality rule configuration files by the following steps:

Select Data Quality > Metric Quality > Rule Config from the left navigation pane of Application Portal.
In the Quality Rule Configuration section, select Download the Template.

Open the downloaded template file and configure the following fields.

Field	Required/Optional	Description
Metric ID	Required	The identifier for the metric that requires data quality analysis. You can enter the identifiers of derived or calculated metrics registered in EnOS Metric Management.
Domain	Required	The asset type to which this metric rule applies. You can enter `wind`, `solar`, `building`, `storage`, or `ark`.
Asset Granularity	Required	The asset granularity to which this metric rule applies. You can enter `site`.
Rule Template	Required	The data quality rule template for this metrics rule application. You can enter `Out of Range`.
Rule Configuration	Required	Expression used to analyze the data quality of metrics. You can enter the following operators: `&&`, `\|\|`, `<`, `<=`, `>=`, `+`, `-`, ``, `/`, or `()`. You can enter the following parameters: `a[attribute id]` represents properties,`m[metric id]` represents metrics,`[target]` represents metric data. For example, `[target]>100 && [target]<a[attr]100` represents when the metric data is greater than 100 and less than 100 times of the `attr` attribute value, the data quality issue specified in the Rule Template will occur.

Select Upload in Data Quality > Metric Quality > Rule Config > Quality Rule Configuration.

To modify a quality rule configuration file that already exists in the current application, select Replace in Data Quality > Metric Quality > Quality Rule Configuration to upload the new file.

Quality Analysis Configuration¶

Quality Analysis Configuration specifies the models and measurement points associated to the target metric. It can be used to analyze the root causes of data quality issues for metrics. Data Quality Analysis Configuration is applicable to the following scenarios：

Specifying the measurement points that associated to a metric. Foe example, the Daily Production metric comes from the Total Active Production measurement point on the basic Wind Turbine model. When a data quality issue occurs in Daily Production, it is necessary to check whether the issue is due to the data quality issue in Total Active Production.
When specifying the range of measurement points associated with a metric, it is necessary to further determine the measurement points that are actually used in calculating the metric. For example, when calculating the solar site’s production, the metric production will be determined based on the value of the total production calculation source attribute of the site. To ensure the authenticity and accuracy of the root cause analysis results, the Data Quality Analysis Configuration can be used to specify the model and associated measurement points used to calculate the target metric, avoiding irrelevant measurement points affecting the root cause analysis results. You can use the Attr (Attribute ID = Enumeration Value) for this scenario.
When conducting root cause analysis, it is necessary to check the metrics associated with the specified metric. For example, the monthly production metric is aggregated from daily production data. Therefore, when conducting root cause analysis, it is necessary to check the daily production metric and the original measurement points associated with the daily production metric to ensure accurate root cause analysis. You can use the Metric (Metric ID) for this scenario.

Download, configure, and upload quality analysis configuration files by the following steps:

Select Data Quality > Metric Quality > Rule Config from the left navigation pane of Application Portal.
In the Quality Analysis Configuration section, select Download the Template.

Open the downloaded template file and configure the following fields.

Field	Required/Optional	Description
Metric ID	Required	The identifier of the metric that requires data quality analysis. You can enter the identifiers of the metrics configured in your quality rule configuration file.
Model ID	Optional	The model to which associated measurement point belongs. You can enter the model IDs in EnOS Device Connectivity and Management (DCM).
Point ID	Optional	The measurement point associated to the metric. You can enter the measurement points under the model specified in Model ID.
Additional Conditions	Optional	An expression used to specify the attributes or other metrics associated with the metric. You can enter `Attr (Attribute ID = Enumeration Value)` (as the filter conditions) or `Metric (Metric ID)` (to specify the associated metrics).

Note

When using Metric (Metric ID) expression, ensure that Model ID and Point ID are empty and this Metric ID exists in the metric rule configuration file.

Select Upload in Data Quality > Metric Quality > Rule Config > Quality Analysis Configuration.

To modify a quality analysis configuration file that already exists in the current application, select Replace in Data Quality > Metric Quality > Quality Analysis Configuration to upload the new file.