Edit

Share via

List of statistical operations

  • Article

This article lists statistical operations in the Power Automate Process Mining desktop app.

START()

Returns the start of a process/event/case/path.

Supported context: process, event, case, edge

Output Data Type: DATE

END()

Returns the end of a process/event/case/path.

Supported context: process, event, case, edge

Output Data Type: DATE

DURATION()

Returns the duration of a process/event/case/path.

Supported context: process, event, case, edge

Output Data Type: TIME

EVENTCOUNT()

Returns number of the events in the case/process.

Supported context: process, event

Output Data Type: INT

CASECOUNT()

Returns number of the cases in the process.

Supported context: process

Output Data Type: INT

ACTIVETIME()

Returns case active time.

Supported context: case

Output Data Type: TIME

WAITINGTIME()

Returns case waiting time.

Supported context: case

Output Data Type: TIME

ISPARALLEL()

In the case context, it returns TRUE if at least one event occurred in parallel with another event, otherwise FALSE. In the event context, it returns TRUE if the event occurred in parallel with another event, otherwise FALSE.

Supported context: case, event

Output Data Type: BOOL

ISPARALLELWITH([condition])

Returns TRUE if the event occurred in parallel with another event which fullfilla given condition, otherwise FALSE.

Supported context: event

Parameters:

  • [condition] - condition under which is parallelism accepted

    Data type: BOOLEAN

Output Data Type: BOOL

UTILIZATION()

Returns case utilization (number from 0 to 1).

Supported context: case

Output Data Type: FLOAT

PARALLELUTILIZATION()

Returns the cumulative case utilization (a number from 0 to 1 to N). A value above 1 is due to parallel events that last longer than the case itself.

Supported context: case

Output Data Type: FLOAT

REWORKCOUNT([attributeName])

Returns the total count of all reworks (loops and self-loops) within the case.

Supported context: case

Parameters:

  • [attributeName] - Attribute to calculate repetitions. If none is entered, the default attribute is mining attribute (activity attribute), optional.

    Data type: STRING (only fixed string is allowed)

Output Data Type: INT

LOOPCOUNT([attributeName])

Returns count of loops within the case.

Supported context: case

Parameters:

  • [attributeName] - Attribute to calculate repetitions. If none is entered, the default attribute is mining attribute (activity attribute), optional

    Data type: STRING (only fixed string is allowed)

Output Data Type: INT

SELFLOOPCOUNT([attributeName])

Returns count of self-loops within the case.

Supported context: case

Parameters:

  • [attributeName] - Attribute to calculate repetitions. If none is entered, the default attribute is mining attribute (activity attribute), optional

    Data type: STRING (only fixed string is allowed)

Output Data Type: INT

OCCURRENCE([attributeName])

Returns occurrence index of a given event attribute value within the case.

Supported context: event

Parameters:

  • [attributeName] - Attribute to calculate repetitions. If none is entered, the default attribute is mining attribute (activity attribute), optional

    Data type: STRING (only fixed string is allowed)

Output Data Type: INT

ISSELFLOOP([attributeName])

Returns true when event/edge has self-loop repetition.

Supported context: event, edge

Parameters:

  • [attributeName] - Attribute to calculate repetitions. If none is entered, default attribute is mining attribute (activity attribute), optional

    Data type: STRING (only fixed string is allowed)

Output Data Type: BOOL

ISLOOP([attributeName])

Returns true when event/edge has loop repetition.

Supported context: event, edge

Parameters:

  • [attributeName] - Attribute to calculate repetitions. If none is entered, the default attribute is mining attribute (activity attribute), optional

    Data type: STRING (only fixed string is allowed)

Output Data Type: BOOL

ISREWORK([attributeName])

Returns true when event/edge has any kind of rework (self-loop or loop).

Supported context: event, edge

Parameters:

  • [attributeName] - Attribute name to calculate repetitions. If none is entered, the default attribute is mining attribute (activity attribute), optional

    Data type: STRING (only fixed string is allowed)

Output Data Type: BOOL

ISLOOPINFLOW([attributeName])

Returns true when event/edge has loop inflow.

Supported context: event, edge

Parameters:

  • [attributeName] - Attribute to calculate repetitions. If none is entered, the default attribute is mining attribute (activity attribute), optional

    Data type: STRING (only fixed string is allowed)

Output Data Type: BOOL

ISLOOPOUTFLOW([attributeName])

Returns true when event/edge has loop outflow.

Supported context: event, edge

Parameters:

  • [attributeName] - Attribute to calculate repetitions. If none is entered, the default attribute is mining attribute (activity attribute), optional

Output Data Type: BOOL

LOOPGAIN([attributeName])

Returns difference between the event's loop outflow and loop inflow. Value +1 when the event has loop outflow and no loop inflow. Value -1 when the event has no loop outflow and loop inflow. Otherwise returns 0.

Supported context: event

Parameters:

  • [attributeName] - Attribute name to calculate repetitions. If none is entered, the default attribute is mining attribute (activity attribute), optional

    Data type: STRING (only fixed string is allowed)

Output Data Type: INT

MEDIAN([context],[value],[compression])

Calculates the approximate median of values grouped according to the defined context.

Supported context: process, case, event, edge

Parameters:

  • [context] - defines the context in which the operation is calculated

    Data type: STRING (only fixed string is allowed)

  • [value] - value over which the median is calculated

    Data type: STRING (only fixed string is allowed)

  • [compression] - controls the estimation accuracy and memory utilization. High compression values increase the accuracy of estimation but make the operation slower. The value must be between 20 and 1000, the default value is 200.

    Data type: FLOAT

Output Data Type: INT, FLOAT, DATE, TIME

QUANTILE([context],[value],[q],[compression])

Calculates the approximate q-th quantile of values grouped according to defined context. The q-th quantile of a data set is defined as that value where a q fraction of the data is below that value and (1-q) fraction of the data above that value.

Supported context: process, case, event, edge

Parameters:

  • [context] - defines the context in which the operation is calculated

    Data type: STRING (only fixed string is allowed)

  • [value] - value for evaluation

    Data type: INT, FLOAT, DATE, TIME

  • [q] - quantile to compute, must be between 0 and 1 inclusive.

    Data type: FLOAT (only constant value is allowed)

  • [compression] - controls the estimation accuracy and memory utilization. High compression values increase the accuracy of estimation but make the operation slower. The value must be between 20 and 1000, the default value is 200.

    Data type: FLOAT

Output Data Type: INT, FLOAT, DATE, TIME

CDF([context],[value],[x],[compression])

Calculates the estimated cumulative distribution function (cdf) for the given value from values grouped according to the defined context.

Supported context: case, event, edge

Parameters:

  • [context] - defines the context in which the operation is calculated

    Data type: STRING (only fixed string is allowed)

  • [value] - value for evaluation for cumulative distribution.

    Data type: INT, FLOAT, DATE, TIME

  • [x] - threshold value Data type: INT, FLOAT, DATE, TIME (need to be the same data type as [value] parameter)

  • [compression] - controls the estimation accuracy and memory utilization. High compression values increase the accuracy of estimation but make the operation slower. The value must be between 20 and 1000, the default value is 200.

    Data type: FLOAT

Output Data Type: INT, FLOAT, DATE, TIME

ISFINISHED()

Returns true when the case is categorized as finished (as defined in Process Context – Case Categorization).

Supported context: case

Output Data Type: BOOL

ISRUNNING()

Returns true when the case is categorized as running (as defined in Process Context – Case Categorization)

Supported context: case

Output Data Type: BOOL

ISSTUCK()

Returns true when the case is categorized as stuck (as defined in Process Context – Case Categorization).

Supported context: case

Output Data Type: BOOL

ISINCOMPLETEIMPORT()

Returns true when the case is categorized as import incomplete (as defined in Process Context – Case Categorization)

Supported context: case

Output Data Type: BOOL

STATS([Aggregate]*,[Type]**)

Returns calculated process statistics according to the selected aggregation and type of statistics.

Supported context: process

Parameters:

  • [Aggregate] – aggregation by which the process statistics will be calculated (eg: sum, average, minimum, maximum, range, standard deviation)

  • [Type] - the type of statistics used in the calculation

Output Data Type: INT, FLOAT, TIME, DATE

Types of Aggregations

Following are the allowed aggregation types:

  • Sum
  • Avg
  • Min
  • Max
  • Range
  • Stdev

Types of Statistics

Name Description
CaseStart Case start
CaseEnd Case end
CaseDuration Case Duration
CaseActiveTime Case Active Time
CaseWaitingTime Case Waiting Time
CaseUtilization Case Utilization
EventCount Event Count