Creating a Dataset

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Creating a Dataset


Datasets for Automation Service, is an application which lets you group business information to make sure data preparation in its storage, and use it for a specific purpose (e.g. a specific report or for AI analysis), while easily configuring how and when the information is extracted from processes in Bizagi.

For introductory information on this application, refer to Bizagi datasets.


Datasets for Automation Service lets you expose and save in Automation Service, your Bizagi processes’ business information so you can use it for specific purposes like creating reports with third party tools or for AI analysis.

You can easily configure how and when the information is extracted from processes in Bizagi to make sure data preparation (cleaning, selecting data) is complete and that your Datasets to contain high-quality data which is final and reliable when consumed.


This section describes how to get started with Datasets, and create a new Dataset.



To create a new Dataset, follow these steps:


1. Log in to the Management portal.

To log in, recall that you need an account at which belongs to your corporate subscription, as created by your Automation Service subscription owner, and as described at User access and registration.




2. Enter your subscription details.

Once you log in, on the landing page you see a list of your current subscriptions. Click the one you want to work with.




3. Go to the Datasets page.

In the list of projects in your subscription, go to the Datasets tab and click Go to Project Board.




4. Create a new Dataset project.

Click the plus icon to Add project.




Give the Dataset project a Name and a meaningful Description, and click Create Project when you are ready.


A Dataset project is not related to a Bizagi project and its processes.

A Dataset project's main purpose is to help you organize and manage the Datasets you may have.


5. Create a new dataset.

Click the New dataset option for a given Dataset project,  




Give the Dataset a Name and a meaningful Description, and define the columns structure for that Dataset.

You can either load a .csv file for the Dataset to take the file's columns as definitions, or you manually define columns.




Defining the structure from a csv

If using the .csv option, click Select a csv option to upload your file from its location:




The Dataset automatically detects the Data type of each column.




However, it is important that you double-check that each column is set with the appropriate Data type. If there is a problem, you can manually change a column's definition.

You can choose String, Numeric, Boolean or Datetime as the Data type.




Click Create dataset to finish up.


Defining the structure manually

Click Create a schema manually to define each of the columns by using the Add new column option and choosing its Data type:




You can choose String, Numeric, Boolean or Datetime as the Data type.

Click Create dataset to finish up.



Regardless of how the structure was defined, you can update it by adding extra columns manually. For more information, refer to Adding a column to an existing Dataset.


At this point, your Dataset will be created, and you can start using it right away.

The created Dataset should appear under a Dataset project, and you can find its three default environments: Development, testing and production.




In order to learn about these different environments and their use, refer to Dataset environments.