- 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
- Triggering an automation from a process app
- Viewing Process data
- Creating apps
- Loading data
- Customizing process apps
- App templates
- Additional resources
- Out-of-the-box Tags and Due dates
- Editing data transformations in a local environment
- Setting up a local test environment
- Designing an event log
- Extending the SAP Ariba extraction tool
- Performance characteristics
Process Mining
Defining new input tables
Follow these steps to add a new table that was added to your input data.
Make sure the input data needed for your new table is available in your app. See also Loading data.
-
Go to the Data transformations editor.
-
Add the new input table to the
sources.yml
file. -
Add a new file for the input table in the models -> 1_input section of the Transformations.
-
Add the fields in the
select
statement.Tip:Use thepm_utils.mandatory
andpm_utils.optional
macros to define mandatory and optional fields from the pm_utils library.pm_utils.mandatory
Loads and type-casts a column. If the source column does not exist, an error is thrown. pm_utils.optional
Loads and type-casts a column. If the source column does not exist, a column is created with value NULL. -
For each field:
-
Set the correct field type. For example
, 'double'
. -
Name the field using an alias. For example
as "Case_ID"
.Below is an example of a table definition.
/* Some fields in this table are optional. These fields are created in the SQL if they do not exist in the source data. */ with Cases_input as ( select -- Mandatory {{ pm_utils.mandatory(source_table, '"Case_ID"') }} as "Case_ID", -- Optional {{ pm_utils.optional(source_table, '"Case"') }} as "Case", {{ pm_utils.optional(source_table, '"Case_status"') }} as "Case_status", {{ pm_utils.optional(source_table, '"Case_type"') }} as "Case_type", {{ pm_utils.optional(source_table, '"Case_value"', 'double') }} as "Case_value" from {{ source_table }} ) select*from Cases_input
/* Some fields in this table are optional. These fields are created in the SQL if they do not exist in the source data. */ with Cases_input as ( select -- Mandatory {{ pm_utils.mandatory(source_table, '"Case_ID"') }} as "Case_ID", -- Optional {{ pm_utils.optional(source_table, '"Case"') }} as "Case", {{ pm_utils.optional(source_table, '"Case_status"') }} as "Case_status", {{ pm_utils.optional(source_table, '"Case_type"') }} as "Case_type", {{ pm_utils.optional(source_table, '"Case_value"', 'double') }} as "Case_value" from {{ source_table }} ) select*from Cases_input
-
To make the new fields available for use in your dashboards, the fields must be added to an output table. See Adding fields for a description on how to create output fields.
Below is an overview of the different field types and their default format settings.
Field type |
Format |
---|---|
boolean |
true , false , 1 , 0 |
date |
yyyy-mm-dd (default)
|
datetime |
yyyy-mm-dd hh:mm:ss[.ms] , where [.ms] is optional. (default)
|
double |
Decimal separator:
. (dot)
Thousand separator: none |
integer |
Thousand separator: none |
text |
N/A |