- 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
- Transforming data- Adding input tables
- Deleting input tables
- Defining new input tables
 
- Data models
 
- Customizing dashboards
- Publishing Dashboards
- App templates
- Notifications
- Additional resources

Process Mining
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. Check out Loading data.
- 
                     Go to the Data transformations editor. 
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                     Add the new input table to thesources.ymlfile.
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                     Add a new file for the input table in the models -> 1_input section of the Transformations. 
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                     Add the fields in theselectstatement.Tip:Use thepm_utils.mandatoryandpm_utils.optionalmacros to define mandatory and optional fields from the pm_utils library.pm_utils.mandatoryLoads and type-casts a column. If the source column does not exist, an error is thrown. pm_utils.optionalLoads and type-casts a column. If the source column does not exist, a column is created with value NULL. 
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                     For each field:- 
                              Set the correct field type. For example, 'double'.
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                              Name the field using an alias. For exampleas "Case_ID".The following code shows 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
 
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To make the new fields available for use in your dashboards, the fields must be added to an output table. Check out Adding fields for a description on how to create output fields.
The following table describes 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 |