- Release notes
- Before you begin
- Getting started
- Integrations
- Working with process apps
- Working with dashboards and charts
- Working with process graphs
- Working with Discover process models and Import BPMN models
- Showing or hiding the menu
- Context information
- Export
- Filters
- Sending automation ideas to UiPath® Automation Hub
- Tags
- Due dates
- Compare
- Conformance checking
- Root cause analysis
- Simulating automation potential
- Starting a Task Mining project from Process Mining
- Triggering an automation from a process app
- Viewing Process data
- Creating apps
- Loading data
- Customizing process apps
- Publishing process apps
- App templates
- Additional resources
Tags
In Process Mining, tags are the business rules you apply to your data, that enable you to check conformance, such as inefficiencies, rework, or violations, in your process.
Tags
table must be must be present in your dataset.
If you want to use the Tags dashboard to analyze tags in your process, tags must be defined for your app template.
For certain app templates, there are out of the box tags available, which will be shown in the dashboard. In the documentation for your specific app template you will find an overview of the available tags. The App Templates page contains links to the documentation for all available app templates.
All custom process app templates have one tag implemented out of the box that checks whether a case has rework activities that are executed by different users.
If no data is available in the Tags dashboard, you need to configure your own tags using data transformations. Here you can also configure any default tags to your business needs. Below is an overview of the tags configuration files for the different app templates.
App templates based on |
Tags configuration file |
Event log | models\5_business_logic\Tags_base.sql |
Custom process 1 | models\5_business_logic\Tags_base.sql |
Purchase-to-Pay | models\5_business_logic\Tags.sql |
Order-to-Cash | models\5_business_logic\Tags.sql |
Tags_raw.csv
file. See Custom process input fields.
In the last transformation step, business logic is added as needed for data analysis.
Each record in the tags table represents one tag for a certain case. Example tags are:
- SLA violation for a contract.
- a payment done by an unauthorized person.
Case_ID
, and Tag
.
Not all cases will have a tag and some cases may have multiple tags.
Refer to Data transformations for more information.
Below are some SQL examples that you can use to configure Tags using transformations.
Case_ID
. If you want to use the SQL examples to define Tags for Purchase-to-Pay app templates or Order-to-Cash app templates, make sure to use the appropriate entity and the related internal entity_ID. When extending the implementation
for Tags, follow the existing implementation.
Directly follows
This SQL code identifies cases where activity 'X' is directly followed by activity 'Y' and tags them as "Violation".
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- Event log with current activity and next activity
Event_log_extended as (
select
Event_log_base."Case_ID",
Event_log_base."Activity" as "Current_activity",
lead(Event_log_base."Activity") over (order by "Event_end") as "Next_activity"
from Event_log_base
),
-- This SQL code checks whether activity X is directly followed by Y in a given case
Directly_follows as (
select
Event_log_extended ."Case_ID",
{{ pm_utils.as_varchar('Activity X directly followed by activity Y') }} as "Tag",
{{ pm_utils.as_varchar('Violation') }} as "Tag_type"
from Event_log_extended
where Event_log_extended ."Current_activity" = 'X' and Event_log_extended ."Next_activity" = 'Y'
group by Event_log_extended ."Case_ID"
)
select * from Directly_follows
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- Event log with current activity and next activity
Event_log_extended as (
select
Event_log_base."Case_ID",
Event_log_base."Activity" as "Current_activity",
lead(Event_log_base."Activity") over (order by "Event_end") as "Next_activity"
from Event_log_base
),
-- This SQL code checks whether activity X is directly followed by Y in a given case
Directly_follows as (
select
Event_log_extended ."Case_ID",
{{ pm_utils.as_varchar('Activity X directly followed by activity Y') }} as "Tag",
{{ pm_utils.as_varchar('Violation') }} as "Tag_type"
from Event_log_extended
where Event_log_extended ."Current_activity" = 'X' and Event_log_extended ."Next_activity" = 'Y'
group by Event_log_extended ."Case_ID"
)
select * from Directly_follows
Indirectly follows
This SQL code identifies cases where activity 'X' is directly or indirectly followed by activity 'Y' and tags them as "Violation".
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
Cases_with_activity_X as (
select
Event_log_base."Case_ID",
min(Event_log_base."Event_end") as "Event_end"
from Event_log_base
where Event_log_base."Activity" = 'X'
group by Event_log_base."Case_ID"
),
-- Activity X is directly or indirectly followed by activity Y
Indirectly_follows as (
select
Event_log_base."Case_ID",
{{ pm_utils.as_varchar('Activity X indirectly followed by activity Y') }} as "Tag",
{{ pm_utils.as_varchar('Violation') }} as "Tag_type"
from Event_log_base
inner join Cases_with_activity_X
on Event_log_base."Case_ID" = Cases_with_activity_X."Case_ID"
where Event_log_base."Activity" = 'Y' and Event_log_base."Event_end" > Cases_with_activity_X."Event_end"
group by Event_log_base."Case_ID"
)
select * from Indirectly_follows
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
Cases_with_activity_X as (
select
Event_log_base."Case_ID",
min(Event_log_base."Event_end") as "Event_end"
from Event_log_base
where Event_log_base."Activity" = 'X'
group by Event_log_base."Case_ID"
),
-- Activity X is directly or indirectly followed by activity Y
Indirectly_follows as (
select
Event_log_base."Case_ID",
{{ pm_utils.as_varchar('Activity X indirectly followed by activity Y') }} as "Tag",
{{ pm_utils.as_varchar('Violation') }} as "Tag_type"
from Event_log_base
inner join Cases_with_activity_X
on Event_log_base."Case_ID" = Cases_with_activity_X."Case_ID"
where Event_log_base."Activity" = 'Y' and Event_log_base."Event_end" > Cases_with_activity_X."Event_end"
group by Event_log_base."Case_ID"
)
select * from Indirectly_follows
Activity X multiple times
This SQL code identifies cases where activity 'X' occurs more than once, and tags them as "Inefficiency".
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- This SQL code checks if Activity X occurs twice or more times in the same case
Activity_X_multiple_times as (
select
Event_log_base."Case_ID",
{{ pm_utils.as_varchar('Activity X multiple times') }} as "Tag",
{{ pm_utils.as_varchar('Inefficiency') }} as "Tag_type"
from Event_log_base
where Event_log_base."Activity" = 'X'
group by Event_log_base."Case_ID"
having count(Event_log_base."Activity") > 1
)
select * from Activity_X_multiple_times
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- This SQL code checks if Activity X occurs twice or more times in the same case
Activity_X_multiple_times as (
select
Event_log_base."Case_ID",
{{ pm_utils.as_varchar('Activity X multiple times') }} as "Tag",
{{ pm_utils.as_varchar('Inefficiency') }} as "Tag_type"
from Event_log_base
where Event_log_base."Activity" = 'X'
group by Event_log_base."Case_ID"
having count(Event_log_base."Activity") > 1
)
select * from Activity_X_multiple_times
Case has activity X
This SQL code identifies cases that have one or more activities with a name that contains 'X', and tags them as "Inefficiency".
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- Case has activity with name like X
Case_has_activity_X as (
select
Event_log_base."Case_ID",
{{ pm_utils.as_varchar('Case has activity X') }} as "Tag",
{{ pm_utils.as_varchar('Inefficiency') }} as "Tag_type"
from Event_log_base
where {{ pm_utils.charindex('X', 'Event_log_base."Activity"') }} > 0
group by Event_log_base."Case_ID"
)
select * from Case_has_activity_X
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- Case has activity with name like X
Case_has_activity_X as (
select
Event_log_base."Case_ID",
{{ pm_utils.as_varchar('Case has activity X') }} as "Tag",
{{ pm_utils.as_varchar('Inefficiency') }} as "Tag_type"
from Event_log_base
where {{ pm_utils.charindex('X', 'Event_log_base."Activity"') }} > 0
group by Event_log_base."Case_ID"
)
select * from Case_has_activity_X
Case has no activity X
This SQL code identifies cases for which there are no activities that have a name containing 'X' and tags them as "Inefficiency".
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
Cases as (
select * from {{ ref('Cases') }}
),
-- Case has no activity with name like X
-- Obtained by subtracting the set of cases that have activity X from the set of all cases
Case_has_no_activity_X as (
select
Cases."Case_ID",
{{ pm_utils.as_varchar('Case has no activity X') }} as "Tag",
{{ pm_utils.as_varchar('Inefficiency') }} as "Tag_type"
from Cases
where Cases."Case_ID" not in (
-- Case has activity with name like X
select
Event_log_base."Case_ID"
from Event_log_base
where {{ pm_utils.charindex('X', 'Event_log_base."Activity"') }} > 0
group by Event_log_base."Case_ID"
)
)
select * from Case_has_no_activity_X
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
Cases as (
select * from {{ ref('Cases') }}
),
-- Case has no activity with name like X
-- Obtained by subtracting the set of cases that have activity X from the set of all cases
Case_has_no_activity_X as (
select
Cases."Case_ID",
{{ pm_utils.as_varchar('Case has no activity X') }} as "Tag",
{{ pm_utils.as_varchar('Inefficiency') }} as "Tag_type"
from Cases
where Cases."Case_ID" not in (
-- Case has activity with name like X
select
Event_log_base."Case_ID"
from Event_log_base
where {{ pm_utils.charindex('X', 'Event_log_base."Activity"') }} > 0
group by Event_log_base."Case_ID"
)
)
select * from Case_has_no_activity_X
Starts with
This SQL code identifies cases that start with activity 'X' and tags them as "Violation".
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- Add row_number to initial event log
Event_log_base_numbered as (
select
Event_log_base."Case_ID",
Event_log_base."Activity",
Event_log_base."Event_end",
row_number() over (partition by Event_log_base."Case_ID" order by Event_log_base."Event_end") as "Row_number"
from Event_log_base
),
-- Case starts with activity X
Starts_with as (
select
Event_log_base_numbered."Case_ID",
{{ pm_utils.as_varchar('Case starts with activity X') }} as "Tag",
{{ pm_utils.as_varchar('Violation') }} as "Tag_type"
from Event_log_base_numbered
where
Event_log_base_numbered."Row_number" = 1
and Event_log_base_numbered."Activity" = 'X'
)
select * from Starts_with
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- Add row_number to initial event log
Event_log_base_numbered as (
select
Event_log_base."Case_ID",
Event_log_base."Activity",
Event_log_base."Event_end",
row_number() over (partition by Event_log_base."Case_ID" order by Event_log_base."Event_end") as "Row_number"
from Event_log_base
),
-- Case starts with activity X
Starts_with as (
select
Event_log_base_numbered."Case_ID",
{{ pm_utils.as_varchar('Case starts with activity X') }} as "Tag",
{{ pm_utils.as_varchar('Violation') }} as "Tag_type"
from Event_log_base_numbered
where
Event_log_base_numbered."Row_number" = 1
and Event_log_base_numbered."Activity" = 'X'
)
select * from Starts_with
Throughput time longer than 10 days
This SQL code identifies cases for which the throughput time is longer than 10 days and tags them as "Inefficiency".
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- Throuput time of each case
Throughput_time_per_case as (
select
Event_log_base."Case_ID",
{{ pm_utils.datediff('day', 'coalesce(min(Event_log_base."Event_start"), min(Event_log_base."Event_end"))', 'max(Event_log_base."Event_end")') }} as "Throughput_time"
from Event_log_base
group by Event_log_base."Case_ID"
),
-- Case throughput time is longer than 10 days
Throughput_time_longer_than_10_days as (
select
Throughput_time_per_case."Case_ID",
{{ pm_utils.as_varchar('Throughput time is longer than 10 days') }} as "Tag",
{{ pm_utils.as_varchar('Inneficiency') }} as "Tag_type"
from Throughput_time_per_case
where Throughput_time_per_case."Throughput_time" > 10
)
select * from Throughput_time_longer_than_10_days
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- Throuput time of each case
Throughput_time_per_case as (
select
Event_log_base."Case_ID",
{{ pm_utils.datediff('day', 'coalesce(min(Event_log_base."Event_start"), min(Event_log_base."Event_end"))', 'max(Event_log_base."Event_end")') }} as "Throughput_time"
from Event_log_base
group by Event_log_base."Case_ID"
),
-- Case throughput time is longer than 10 days
Throughput_time_longer_than_10_days as (
select
Throughput_time_per_case."Case_ID",
{{ pm_utils.as_varchar('Throughput time is longer than 10 days') }} as "Tag",
{{ pm_utils.as_varchar('Inneficiency') }} as "Tag_type"
from Throughput_time_per_case
where Throughput_time_per_case."Throughput_time" > 10
)
select * from Throughput_time_longer_than_10_days
Duration more than 30 minutes
This SQL code identifies cases where the time duration between activity 'X' and 'Y' is more than 30 minutes and tags them as "Inefficiency".
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- First activity X of each case
First_activity_X_of_each_case as (
select
Event_log_base."Case_ID",
min(Event_log_base."Event_end") as "Event_end"
from Event_log_base
where Event_log_base."Activity" = 'X'
group by Event_log_base."Case_ID"
),
-- Last activity Y of each case
Last_activity_Y_of_each_case as (
select
Event_log_base."Case_ID",
max(Event_log_base."Event_end") as "Event_end"
from Event_log_base
where Event_log_base."Activity" = 'Y'
group by Event_log_base."Case_ID"
),
-- Time between first X and last Y > 30 minutes
Duration_more_than_30_minutes as (
select
First_activity_X_of_each_case."Case_ID",
{{ pm_utils.as_varchar('Duration more than 30 minutes') }} as "Tag",
{{ pm_utils.as_varchar('Inefficiency') }} as "Tag_type"
from First_activity_X_of_each_case
inner join Last_activity_Y_of_each_case
on First_activity_X_of_each_case."Case_ID" = Last_activity_Y_of_each_case."Case_ID"
where {{ pm_utils.datediff('minute', 'First_activity_X_of_each_case."Event_end"', 'Last_activity_Y_of_each_case."Event_end"') }} > 30
)
select * from Duration_more_than_30_minutes
with Event_log_base as (
select * from {{ ref('Event_log_base') }}
),
-- First activity X of each case
First_activity_X_of_each_case as (
select
Event_log_base."Case_ID",
min(Event_log_base."Event_end") as "Event_end"
from Event_log_base
where Event_log_base."Activity" = 'X'
group by Event_log_base."Case_ID"
),
-- Last activity Y of each case
Last_activity_Y_of_each_case as (
select
Event_log_base."Case_ID",
max(Event_log_base."Event_end") as "Event_end"
from Event_log_base
where Event_log_base."Activity" = 'Y'
group by Event_log_base."Case_ID"
),
-- Time between first X and last Y > 30 minutes
Duration_more_than_30_minutes as (
select
First_activity_X_of_each_case."Case_ID",
{{ pm_utils.as_varchar('Duration more than 30 minutes') }} as "Tag",
{{ pm_utils.as_varchar('Inefficiency') }} as "Tag_type"
from First_activity_X_of_each_case
inner join Last_activity_Y_of_each_case
on First_activity_X_of_each_case."Case_ID" = Last_activity_Y_of_each_case."Case_ID"
where {{ pm_utils.datediff('minute', 'First_activity_X_of_each_case."Event_end"', 'Last_activity_Y_of_each_case."Event_end"') }} > 30
)
select * from Duration_more_than_30_minutes
The Tags dashboard enables you to analyze the tags that occur in the process.
Follow these steps to display the Tags dashboard.
-
Select Tags in the menu on the left of the dashboard.
The Tags dashboard is displayed.
Metrics
Below is a description of the metrics that can be used to analyze the cases regarding tags.
Metric |
Description |
---|---|
Number of cases |
The number of cases that have the tag assigned. |
Number of tags |
The number of tags assigned. |