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Test Author Guide
This guide describes how to create and edit test assets in HCL DevOps Test Hub (Test Hub), and then publish test assets to the remote Git repository that you have configured in your project. This guide is intended for testers and test managers.
Working with Datasets on DevOps Test Hub
You can find information about creating datasets in HCL DevOps Test Hub (Test Hub), applying a dataset classification, editing datasets, and managing datasets that are in your project repository.

Test Author Guide
This guide describes how to create and edit test assets in HCL DevOps Test Hub (Test Hub), and then publish test assets to the remote Git repository that you have configured in your project. This guide is intended for testers and test managers.
- Edit branch overview
  When you want to create or modify a test resource in HCL DevOps Test Hub (Test Hub), you must use an Edit branch. An Edit branch is a temporary branch of the branch in the project repository into which you want to add the created resource or edited resource.
- Data overview
  When you want to create realistic test scenarios that can simulate real-world or practical situations, you can use the data fabrication feature in HCL DevOps Test Hub (Test Hub) to fabricate test data. You can also create or edit datasets that pass variable data to tests at test run time.
- Working with Datasets on DevOps Test Hub
  You can find information about creating datasets in HCL DevOps Test Hub (Test Hub), applying a dataset classification, editing datasets, and managing datasets that are in your project repository.
  - Creating a dataset
    You can create datasets in HCL DevOps Test Hub (Test Hub) to replace the values of existing dataset with the values of new dataset during a test or schedule run.
  - Creating a dataset by using a CSV file
    When you use variable data that is contained in a CSV file, you can import the data from the CSV file and create a dataset in HCL DevOps Test Hub (Test Hub).
  - Creating a dataset by using a Data definition
    When you created a Data definition in HCL DevOps Test Hub (Test Hub) to fabricate test data, you can create a dataset by using the Data definition.
  - Editing a dataset
    You can add, modify, remove, import, or export data from a dataset.
  - Dataset encryption
    Encrypted datasets are useful when you want to run tests that contain confidential information such as a set of passwords or account numbers.
  - Publishing changes in datasets
    After you create, edit, or encrypt datasets in HCL DevOps Test Hub (Test Hub), you can publish all changes made to a dataset to a branch in the project. After you publish the dataset, other members in the project can use your dataset in their test run, if required. The Edit branch automatically disappears from the Branch list and changes made to the datasets are merged into the selected branch of the project repository.
  - Viewing a dataset
    When test assets includes datasets, you can view the contents of a dataset from HCL DevOps Test Hub (Test Hub). The datasets residing in the Git repository are listed in the Datasets page.
  - Deleting a dataset
    You can delete the dataset when it is not required in your test environment.
  - Viewing an encrypted dataset
    You can use the Dataset page to view the contents of an encrypted dataset from HCL DevOps Test Hub (Test Hub).
  - Changing classification for an encrypted dataset
    To move the encrypted dataset from one classification to another dataset in HCL DevOps Test Hub (Test Hub), you can change the classification for an encrypted dataset.
  - Managing an encrypted dataset
    You can use encrypted datasets to limit access to confidential information such as account number or passwords. You can arrange data by an appropriate category so that project members can use datasets more effectively in certain tests and protect them.
- Data fabrication
  Test data is the core component of any application testing. It is very time-consuming to create test data manually. You can use the data fabrication feature in HCL DevOps Test Hub (Test Hub) to create realistic datasets for comprehensive testing scenarios. The feature provides data fabrication capabilities that can help you to generate synthetic data quickly and efficiently without the risk of data leaks or privacy issues.

Working with Datasets on DevOps Test Hub

You can find information about creating datasets in HCL DevOps Test Hub (Test Hub), applying a dataset classification, editing datasets, and managing datasets that are in your project repository.

A dataset contains variable data that are used by a test at test run time. You create the datasets and associate them with your tests in the desktop products. You can decide whether you want to use the dataset associated with the test to be used at run time or override that associated dataset with another dataset at run time. You can create datasets in the desktop products itself and select the datasets as overrides in the desktop products.

When you want to run those tests from Test Hub and you want the tests to use a different set of variable data, you can create datasets in Test Hub. You can then select them to override the dataset associated with the tests that are in the project repository.

You can create a dataset in Test Hub by using any of the following methods:

Creating an empty dataset. See Creating a dataset.
Importing data from a CSV file. See Creating a dataset by using a CSV file.
Creating a dataset with fabricated data. See Creating a dataset by using a Data definition.

When you want to edit the data in a dataset, you must open it for editing. See Editing a dataset.

After you edit the dataset, you must publish the changes, so that the dataset is added to the project repository. See Publishing changes in datasets.

If the data in your dataset contains sensitive information, you can encrypt the dataset columns. See Encrypting a dataset column.

If a dataset has encrypted columns and you want to view an encrypted dataset, see Viewing an encrypted dataset.

When you want to remove the encryption for dataset columns, you can decrypt the dataset column. See Decrypting a dataset column.

You can assign a classification for encrypted datasets. See Managing an encrypted dataset.

You can change the classification of an encrypted dataset. See Changing classification for an encrypted dataset.