To secure test data, you must encrypt datasets. You can encrypt
data in the columns of a dataset by using an encryption key. When you run a test
that utilizes a dataset with encrypted variables, you must enter the encryption key
for the encrypted column that the test uses.
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Log in to Rational Test Automation
Server.
The team space that contains your project is displayed.
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Click to open the project that contains the test assets.
The Overview page of the project is
displayed.
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Click .
The Data page and the Data navigator are
displayed.
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Select the branch that contains your project with the datasets that you want to
edit.
The projects in the selected branch are displayed in the Data navigator. The
datasets are listed under the folder you created to contain the dataset
within a logical folder named Datasets.
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Click the dataset in the data navigator.
The dataset opens in the right pane.
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Click Edit.
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Select your action to either select an existing Edit branch or create
an Edit branch:
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Right-click any cell in a column that you want to encrypt and select
Encrypt column data.
The Encrypt Column window is
displayed.
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Enter an encryption key in the Encryption Key field to encrypt the
data in the column.
Remember: When you have already encrypted other columns in the dataset, you must
enter the same encryption key that you used previously. You can use only one encryption key to
encrypt columns in a dataset.
Important:
The encryption keys that you use to encrypt data in a dataset are not stored on
the server nor can be retrieved from the server. Therefore, you must remember to
store the encryption keys in a secure location. You must use the same encryption
keys to perform the following operations:
-
Click Encrypt Column.
Asterisks are displayed instead of actual data for the encrypted
column.
-
Click the Save icon
to save the changes to the dataset.
You have encrypted the dataset column in your project.
You can publish the dataset to the Git repository
so that other members of the project can use the dataset by clicking the
Publish icon
. See Publishing changes in datasets.