Manage datasets in Postman

You can manage your datasets to keep their data sources and views current. As your workflows evolve, you can add new data sources, update existing ones, and modify views to control how data is retrieved and used in your tests, scripts, and mock servers.

Manage datasets

You can manage a dataset to update its details or make changes to how it’s stored in your workspace. In Local View, each dataset is defined by a YAML file in your local Git repository, which includes its data sources and views.

To manage a dataset, do the following:

1. Click Items in the sidebar.
2. Click Datasets.
3. Next to a dataset, click View more actions.

You can perform the following actions:

• Rename — Change the dataset’s name.
• Add source — Open the dataset’s overview to add a new data source or update an existing one. Learn more about managing data sources.
• Edit YAML — (Local View only) Open and edit the dataset’s YAML file directly. This file defines the dataset’s data sources and views and is stored in your local Git repository. The file also includes metadata about the dataset, such as its name and ID.
• Delete — Remove the dataset from your workspace.

Manage data sources

You can expand an existing dataset by adding a new data source. You can also view a data source to see its details, or update its configuration if it’s a MySQL, Postgres, or SQL Server data source. You can also remove a data source from a dataset.

Add a new data source

To add a new data source, do the following:

1. Click Items in the sidebar.
2. Click Datasets.
3. Select a dataset to open its overview. You can also click View more actions next to a dataset, then select Add source.
4. Click Add source, then select the data source type you’d like to add.
5. Configure the data source and add it to your dataset.
6. (Optional) Add more data sources to combine different types of data in your workflows.

To remove a data source from a dataset, hover over the data source, click , and then click Delete to confirm. Make sure to update any views that use the data source because deleting it will break those views.

View and update an existing data source

You can view an existing data source. You can also update a data source’s configuration if it’s an external or custom data source.

To view and update a data source, do the following:

1. Click Items in the sidebar.
2. Click Datasets.
3. Select a dataset to open its overview.
4. Click a data source to open it in a new tab.
5. Update the data source:
   • If the data source is an external data source, you can update its connection details. Click the Settings tab, update the connection details, and click Refresh to update the preview. You can view the preview from the Data tab.
   • If the data source is a local file, click Change to select a different file, preview the data, then click Save. Postman supports CSV, JSON, and spreadsheet files. Uploaded Postman cloud files are read-only, so you can view the data but can’t change the file.

Update a data source with Agent Mode

You can use Agent Mode to add new data sources or update existing ones with sample data. This is useful when you want to quickly refresh test data or expand a dataset without manually editing files or database records.

Agent Mode can create or update CSV or JSON data files with additional or modified data. For example, you could ask Agent Mode the following:

If you have a connected database, you can use Agent Mode to generate and insert sample data into existing tables. For example, you could ask:

After updating the data source, you can refresh the data source and update your views as needed to reflect the changes.

Manage views

You can add a new view or update an existing one to change how data is retrieved from your dataset. A view defines how data is filtered, combined, or transformed for your workflows. For example, you might update a view’s query to return only a subset of data from the data source, or to create new columns based on existing data.

Views can retrieve data from multiple data sources. However, views can’t combine data from local data sources and cloud data sources.

To add or update a view, do the following:

1. Click Items in the sidebar.

2. Click Datasets.

3. Select a dataset to open its overview.

4. Choose from the following:

   • To add a new view, click Create view. In the dialog, enter a name, select the sources the view queries, then click Create view.
   • To update an existing view, click the view.

5. Enter or edit the SQLite-compatible query that defines how the data is retrieved from the data source. To learn more about writing queries, see Example dataset views.

6. Click Run to run the query and preview the results in the table pane. You can also search the results.

7. Save your changes:

   • To save your changes to the current view, click Update.
   • To save your changes as a separate view without changing the current one, click Save as new view.
   • To discard your changes and revert to the last saved query, click Reset.

Next to a view, you can click View more actions to do the following:

• Rename — Change the view’s name.
• Ask AI — Open Agent Mode with context about the view to help you understand or debug it.
• Preview — Preview a subset of the data returned by the view’s query.
• Delete — Remove the view from the dataset. This doesn’t delete the underlying data source, but it does remove the view’s query and any transformations it applies to the data.

Share a dataset

In Cloud View, you can share a dataset with your team to use in their tests, scripts, and mock servers. You can share a direct link to a dataset, data source, or view.

To share a dataset, do the following:

1. Click Items in the sidebar.
2. Click Datasets.
3. Select a dataset to open its overview.
4. In the upper right, click Copy link to this dataset.

To share a data source or view, click it to open it in a new tab, then click Copy link to this source/view.

Push and pull datasets

You can push and pull datasets to and from the Postman Cloud to share them with your team or access them from different devices.

When you push a dataset, Postman syncs the latest version of the dataset from your local workspace to the Postman Cloud. Local files that are pushed to the Postman Cloud become cloud files.

When you pull a dataset, Postman syncs the latest version of the dataset from the Postman Cloud to your local workspace. Cloud files that are pulled to your local workspace become local files in your Git repository.

Learn more about pushing and pulling changes in Postman.

Troubleshoot datasets

If you encounter issues when working with datasets, use the following troubleshooting steps to identify and resolve common problems.

The error icon (!) may appear next to a dataset in the left sidebar in the following scenarios:

• Dataset is out of sync — This can happen if you edit dataset files outside of Postman or if there are unresolved merge conflicts. Restart Postman to resync the dataset with your local files.

• Invalid or corrupted dataset files — This can happen if the dataset files have invalid formatting or content. Check the files in your local Git repository for formatting issues, or restore them from a previous commit if recent changes caused the issue.

If you have any issues with your datasets, contact Postman support.