Process-Based Dimensions and Measures in YAML

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Process-Based Dimensions and Measures in YAML

Process-based dimensions and measures are defined in YAML format under the value key. This page describes the key-value pairs used within this key.

Process-Based Dimensions

Start Time and End Time

These dimensions display data based on the start or end time of an event or process. They are used to analyze temporal dynamics with the desired level of detail.

Key	Type	Definition
`templateName`	enum	Predefined date/time display template. Possible values: `dateTime`, `date`, `year`, `yearAndQuarter`, `quarter`, `yearAndMonth`, `month`, `dayOfMonth`, `week`, `dayOfWeek`, `hour`
`mode`	enum	Time calculation mode: - `START_TIME` — event/process start time - `END_TIME` — event/process end time
`eventTimeFormula`	string	Value from the Time field of the process table. Format: `'"TableName"."ColumnName"'`
`eventNameFormula`	string	Value from the Event field of the process table. Format: `'"TableName"."ColumnName"'`
`caseCaseIdFormula`	string	Value from the CaseID field of the process. Format: `'"TableName"."ColumnName"'`
filters	array	Predefined filters (optional). If no filters are set, specify an empty list: `filters: []`
`eventName`	string	Event name
`processKey`	string	Process key

Number of Executions or Reworks

This dimension shows how many times an event was executed or how many reworks occurred in a process. Useful for analyzing workload and repetitive actions.

Key	Type	Definition
`templateName`	enum	Predefined aggregation template. Possible values: - `countExecutions` — number of executions - `countReworks` — number of reworks
`mode`	enum	Calculation mode: `AGGREGATION` — aggregation over process data
`eventName`	string	Event name
`processKey`	string	Process key
`caseCaseIdFormula`	string	Value from the CaseID field of the process. Format: `'"TableName"."ColumnName"'`
`eventNameFormula`	string	Value from the Event field of the process table. Format: `'"TableName"."ColumnName"'`
filters	array	Predefined filters (optional). If no filters are set, specify an empty list: `filters: []`

Custom Aggregation in Dimension by Selected Column

Dimensions based on process metrics can be extended with aggregation over any table column. The available predefined formulas (templateName) by data type depend on the dimension or measure data type.

Key	Type	Definition
`mode`	enum	Formula type: `AGGREGATION`
`templateName`	enum	Aggregation method for the selected field. For numeric values: `avg`, `median`, `min`, `max`, `sum`, `count`, `countDistinct`, `top` For temporal values: `firstValue`, `lastValue`, `dateTime`, `date`, `year`, `yearAndQuarter`, `quarter`, `yearAndMonth`, `month`, `dayOfMonth`, `week`, `dayOfWeek`, `hour`
`eventName`	string	Event name
`processKey`	string	Process key
`caseCaseIdFormula`	string	Value from the CaseTable.CaseID field of the process. Format: `'"TableName"."ColumnName"'`
`eventNameFormula`	string	Value from the Event field of the process. Format: `'"TableName"."ColumnName"'`
`eventTimeFormula`	string	Value from the Time field of the process. Format: `'"TableName"."ColumnName"'`. If absent, use `null`
filters	array	Predefined filters (optional). If no filters are set, specify an empty list: `filters: []`
`tableName`	string	Table name
`columnName`	string	Column name

Process-Based Measures

Conversion

This measure calculates conversion between two events: from start to end. It helps evaluate the share of cases that reach a specific stage.

Key	Type	Definition
`mode`	enum	Formula type: `CONVERSION`
`startEventProcessKey`	string	Start process key
`startEventNameFormula`	string	Start event. Format: `'"TableName"."ColumnName"'`
`startEventName`	string	Start event name
`startEventTimeFormula`	string	Start event time from the Time field of the process table. Format: `'"TableName"."ColumnName"'`
startEventFilters	array	Predefined filters for the start event (optional). If none, use: `startEventFilters: []`
`endEventProcessKey`	string	End process key
`endEventNameFormula`	string	End event. Format: `'"TableName"."ColumnName"'`
`endEventName`	string	End event name
`endEventTimeFormula`	string	End event time from the Time field of the process table. Format: `'"TableName"."ColumnName"'`
endEventFilters	array	Predefined filters for the end event (optional). If none, use: `endEventFilters: []`
`endCaseCaseIdFormula`	string	Value from the CaseID field of the end process table. Format: `'"TableName"."ColumnName"'`

Duration

This measure calculates the duration between start and end events (considering whether to use the first or last occurrence). Useful for evaluating stage completion time and comparing durations between events.

Key	Type	Definition
`mode`	enum	Formula type: `DURATION`
`templateName`	enum	Predefined duration aggregation template. Available values: - `avg` — average duration - `median` — median duration
`startEventAppearances`	enum	How to select the start event: - `FIRST` — first occurrence - `LAST` — last occurrence
`startEventProcessKey`	string	Start process key
`startEventNameFormula`	string	Start event. Format: `'"TableName"."ColumnName"'`
`startEventName`	string	Start event name
`startEventTimeFormula`	string	Start event time from the Time field of the process table. Format: `'"TableName"."ColumnName"'`
startEventFilters	array	Predefined filters for the start event (optional). If none, use: `startEventFilters: []`
`endEventAppearances`	enum	How to select the end event: - `FIRST` — first occurrence - `LAST` — last occurrence
`endEventProcessKey`	string	End process key
`endEventNameFormula`	string	End event. Format: `'"TableName"."ColumnName"'`
`endEventName`	string	End event name
`endEventTimeFormula`	string	End event time from the Time field of the process table. Format: `'"TableName"."ColumnName"'`
endEventFilters	array	Predefined filters for the end event (optional). If none, use: `endEventFilters: []`
`endCaseCaseIdFormula`	string	Value from the CaseID field of the end process table. Format: `'"TableName"."ColumnName"'`

Number of Executions or Reworks

This measure calculates the number of executions or reworks and optionally applies an outer aggregation (e.g., average or sum). Used for quantitative assessment of action repetition.

Key	Type	Definition
`outerAggregation`	enum	Outer aggregation of the process metric result. Available values: `avg`, `median`, `count`, `countDistinct`, `min`, `max`, `sum`
`mode`	enum	Formula type: `AGGREGATION`
`templateName`	enum	Predefined process metric template: - `countExecutions` — number of executions - `countReworks` — number of reworks
`processKey`	string	Process key
`caseCaseIdFormula`	string	Value from the CaseID field of the process table. Format: `'"TableName"."ColumnName"'`
`eventName`	string	Event name
`eventNameFormula`	string	Value from the Event field of the process table. Format: `'"TableName"."ColumnName"'`
filters	array	Predefined filters (optional). If no filters are set, specify an empty list: `filters: []`

Custom Aggregation in Measure by Selected Column

Measures based on process metrics can be extended with aggregation over any table field. The available predefined formulas (templateName) by data type depend on the dimension or measure data type.

Key	Type	Definition
`mode`	enum	Formula type: `AGGREGATION`
`outerAggregation`	enum	Outer aggregation of the result: `avg`, `median`, `count`, `countDistinct`, `min`, `max`, `sum`
`templateName`	enum	Base metric for the selected field: `top`, `firstValue`, `lastValue`, `countIf`, `countIfDistinct`
`eventName`	string	Event name
`processKey`	string	Process key
`caseCaseIdFormula`	string	Value from the CaseTable.CaseID field of the process. Format: `'"TableName"."ColumnName"'`
`eventNameFormula`	string	Value from the Event field of the process. Format: `'"TableName"."ColumnName"'`
`eventTimeFormula`	string	Value from the Time field of the process. Format: `'"TableName"."ColumnName"'`. If absent, use `null`
filters	array	Predefined filters (optional). If no filters are set, specify an empty list: `filters: []`
`tableName`	string	Table name
`columnName`	string	Column name

Process Metrics in Filters

Process metrics can be used in filters to select data based on values calculated from process data. For example, you can filter by event or process start/end time or by quantitative metrics like execution or rework counts.

Process metrics in filters can be applied both in views and widgets.

To configure such a metric in a filter, populate the dbDataType, value, and condition parameters. Use dbDataType to specify the formula data type. In the filter condition (condition), specify the filtering method (filteringMethod).

Start Time and End Time

Start and end times in filters are configured similarly to dimensions and measures.

Usage example:

filters:
  - dbDataType: Date
    value:
      templateName: date
      mode: START_TIME
      eventTimeFormula: '"event_log"."event_time"'
      eventNameFormula: '"event_log"."event_name"'
      caseCaseIdFormula: '"case_table"."case_id"'
      filters: []
      eventName: Client questionnaire preparation
      processKey: customer_process
    condition:
      filteringMethod: GREATER_THAN_OR_EQUAL_TO
      values:
        - 2025-12-08 00:00:00

Number of Executions or Reworks

The number of executions or reworks in a filter is configured similarly to the setup for dimensions and measures.

Usage example:

filters:
  - dbDataType: UInt64
    value:
      mode: AGGREGATION
      templateName: countExecutions
      processKey: customer_process
      caseCaseIdFormula: '"case_table"."case_id"'
      eventName: Client proposal approval
      eventNameFormula: '"event_log"."event_name"'
      filters: []
    condition:
      filteringMethod: GREATER_THAN_OR_EQUAL_TO
      values:
        - "50"

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Dimensions and Measures in YAML

Data Formats and Formatting in YAML

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