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Process Mining

Last updated Mar 19, 2025

Data transformations

This page describes how to customize data transformations from within Process Mining. The Data transformations editor is integrated in the dashboard editor. Check out Working with the dashboard editor.

Data transformations enable you to:

  • add new fields for group by and filters. For example, Quality check type.
  • add events. For example, Invoice quality check done.

  • add tags. For example, Failed to meet SLA, Four eyes violation.

  • add business logic for calculating KPIs. For example, Case_has_maverick_buying.

Data transformations editor

The data transformations editor consists of the following sections.

  • Input data

  • Transformations

  • Data model

  • Preview panel

Prerequisites

When starting editing data transformations it is strongly recommended that you:

  • have in-depth knowledge of SQL;

  • are familiar with the source system that is used for data extraction.

Opening Data transformations

  1. Select the Data transformations button in the upper right corner of the dashboard editor to open the Data transformations.

Note:

If you open the in-line editor for the first time, it will take some time to load the editor.

The in-line data transformations editor is displayed.

Transformations

Select Transformations to view the structure of the transformations and to display the .sql files.

Refer to Structure of transformations for more information on the structure of the transformations.

Each .sql file defines a new table in the data model. If you select the a .sql file in the Transformations panel, the SQL query is displayed in the Transformations and a preview of the data file you are editing is displayed in the Preview panel.

When editing a query, you can see a preview of the data of the last time the query was run in the Preview panel.

Important:

If there are any unsaved changes in the transformations, the Save button is enabled. Select Save to save the changes. The status of the transofrmation will be set to Up to date.

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