
This window opens when you click New on the Analytic Data Manager view.
| Property | Value | Description |
|---|---|---|
| Name | text | Provides a descriptive name for the definition. |
| Id | tag | Configures a fully-qualified (namespace:tagName), tag name or tag group name that identifies some specific data in the station, such as hs:zoneAirTempSensor to identify Zone Temp sensors. |
| Aggregation | drop-down list (defaults to First)
|
Configures the default function to apply when the analytic request combines values from multiple data sources into a single
value. This applies to both value and trend requests.
If aggregation is not enabled in the binding/settings window, the aggregation value defined in the Data Definition applies to all chart bindings, reports and tables.
|
| Rollup | drop-down list (defaults to First)
|
Configures the default function to apply when the analytic request needs to rollup records from a single data source into
less granular records.
If rollup is not enabled in the binding/settings window, the rollup value configured in the Data Definition applies to all chart bindings, reports and tables.
|
| Facets | units, precision, min, max, etc. | Configure how to display historical and calculated values, such as units or precision.
A unit is a standard facet that applies to both data input and data output. You use it for viewing a point’s value or algorithm’s result. If a units facet is assigned, it need not match the units facet of a Data Source or Data Definition; however, it must be correct for the raw value being processed and must be convertible to the corresponding unit specified in the Data Definition or Data Source. |
| Missing Data Strategy | additional properties | Configures how the framework handles missing data in a series when processing analytic requests and one or more records are missing for an interval. It applies when even a single record for an interval is missing. It does not apply to value requests. |
| Outlier (Outlier Handling) | Status check boxes (disabled, fault, down, stale, and null are checked by default) | Configures filtering behavior to remove records from a dataset based on the status flags or value of each record. Status values
include: disabled, fault, down, alarm, stale, overridden, null, unackedAlarm and NaN (Not a Number. This is another way, similar
to the InvalidValueFilter block, to filter records based on bad status conditions.
If you check all boxes, the framework filters out all records except those with a status of {ok}, which is always enabled. If you check no box, the framework filters out no records based on status. You may configure additional properties for High Limit and Low Limit (defaults to null check box selected, which does not enforce a limit). This filtering does not apply to value requests. Algorithm blocks may perform additional filtering based on statuses or values. After the framework filters out the records with invalid data, use a missing data strategy to interpolate valid data. |
| RawDataFilter, High Limit | null check box (defaults to checked) or numeric value | Optionally, defines a number above which a data value (an outlier) should be excluded from an analytic calculation.
Setting a limit is similar to using a RangeFilter block in an algorithm where values greater than the high limit are excluded from being processed and using an InvalidValueFilter to filter NaN numbers without the benefit of also filtering infinite values. A use case might be that you have a sensor with a range of 0-150 deg F, any readings above 150 would be anomalies or suspect values, which need to filtered out. |
| RawDataFilter, Low Limit | null check box (defaults to checked) or numeric value | Optionally, defines a number below which a data value (an outlier) should be excluded from an analytic calculation.
Setting a limit is similar to using a RangeFilter block in an algorithm where values lower than the low limit are excluded from being processed and using an InvalidValueFilter to filter NaN numbers without the benefit of also filtering infinite values. A use case might be that you have a sensor with a range of 0-150 deg F, any readings below zero would be anomalies or suspect values, which need to filtered out. |
| Delta Value, High Limit | null check box (defaults to checked) or numeric value | Processes a high-limit delta value from a totalized value. |
| Delta Value, Low Limit | null check box (defaults to checked) or numeric value | Processes a low-limit delta value from a totalized value. |