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Process Mining
Automation CloudAutomation Cloud Public SectorAutomation SuiteStandalone
Last updated Oct 15, 2024

Data transformations

Useful links

Editing transformations locally

When you create a process app from an app template, you want to make sure the data used in the process app reflects your business process in the correct way. With Data transformations you can customize the data used for Process Mining.

You can either customize the transformations from within Process Mining using Data transformations, or you can edit them locally on your desktop, see Editing data transformations in a local environment

This page describes how to customize data transformations from within Process Mining. Data transformations are integrated in the dashboard editor. See 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.

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

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

See 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.

Selecting visible columns

You can select the columns you want to display in the Preview panel.

Follow these steps to change the visible columns.

StepAction

1

Select Columns to display the list of columns.

2

Select the columns you want to display in the Preview panel from the list.

Viewing the transformations Log

The Log panel shows what happens in the background. The Log panel is refreshed automatically every couple of seconds. See the illustration below for an example.
docs image

Log levels

The log contains different log levels to indicate the severity of the message:

Log level

Description

Data run status

Information

An Information message contains helpful information on the progress of the datarun.

Success

Warning

A Warning refers to a potential problem in your data that might affect what will be displayed on a chart in the published process app. It is advised to resolve any warnings to prevent any potential future problems.

Success

Error

An Error refers to a mistake in your data that prevents the process app from loading the data or running the transformations.

You must resolve all errors to enable a successful data run.

Failed

Filtering logs

By default, Errors, Warnings, and Information messages are displayed when you open the Log. You can use the Filter menu to change the log level. See the illustration below for an example.

docs image

Saving the log file

You can select the Copy icon to copy the contents of the log file and paste in, for example, a Notepad file that you can save on your computer. This enables you to view the messages when working on solving the issues causing errors or warnings.

Note:

This also enables you to share the contents of the log file, for example if you need support.

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