Dataset Details Page
Use the Dataset Details page to review a dataset's usage and to perform management tasks on it.
Imported Dataset
For datasets that have been imported into the Alteryx One, you can review source location and metadata information.
Status: For large relational datasets, you can track status of the import process. For more information, go to Overview of Job Monitoring.
Actions:
Preview: Review the first few rows of the dataset.
Make a copy: Create a copy of the imported dataset.
Edit name and description: Edit the name and description for the dataset.
Remove structure: Remove initial steps applied to structure data.
Refresh dataset:If available, this option refreshes the dataset's metadata with the latest source schema.
Note
If you attempt to refresh the schema of a parameterized dataset based on a set of files, only the schema for the first file is checked for changes. If changes are detected, the other files are assumed to contain those changes as well. This can lead to changes being assumed or undetected in later files and potential data corruption.
Data Insights: View key performance metrics for your dataset, change dataset settings specific to Auto Insights, and explore insights about your dataset. To learn more, go to Manage Dataset.
Actions for dataset owners:
Transfer ownership: Transfer ownership of this asset to another users. Go to Transfer Asset Ownership.
Delete dataset:Delete the dataset.
Note
This action only deletes the dataset reference that points to the file in the original data source. It does not delete the dataset in the original data source.
Warning
Deleting a dataset can't be undone.
Reference Dataset
A reference dataset is a reference to the output of a set of transformations, which can be used elsewhere in the application. When the source dataset is modified, the reference dataset automatically receives the changes.
Figure: Reference Dataset details
Actions:
Preview: Review a preview of the first few rows in the dataset.
Edit name and description: Edit the name and description for the dataset.
Delete Reference Dataset: Delete the reference dataset. The object on which the reference dataset is based is untouched.
Warning
Deleting a dataset can't be undone.
Dataset with Parameters
If your dataset was created with parameters, you can review dataset and parameter information in the details.
For more information on creating these datasets, go to Create Dataset with Parameters.
Figure: Dataset with Parameters details
You can review the parameters and variables defined for the dataset.
Action:
Preview: Review the first few rows of the dataset.
Make a copy: Create a copy of the imported dataset.
Edit name and description: Edit the name and description for the dataset.
Edit parameters: Modify the parameters used to create the dataset. Go to Create Dataset with Parameters.
Remove structure: Remove the initial parsing structure. When the structure is removed:
The dataset is converted to an unstructured dataset. An unstructured dataset is the source data converted into a flat file format.
All steps to shape the dataset are removed. You must break up columns in manual steps in any recipe created from the object.
Refresh dataset: If schema refresh is enabled, you can use this option to check for updates to the schema of the dataset source.
Actions for dataset owners:
Transfer ownership: Transfer ownership of this asset to another user. Go to Transfer Asset Ownership.
Delete dataset: Delete the dataset.
Note
This action only deletes the dataset reference that points to the file in the original data source. It does not delete the dataset in the original data source.
Warning
Deleting a dataset can't be undone.
Dataset with SQL
For datasets that were created with SQL statements, the following details are available.
Warning
Through the custom SQL interface, it is possible to enter SQL statements that can delete data, change table schemas, or otherwise corrupt the targeted database. Please use this feature with caution.
Note
If you modify the SQL statement for your imported dataset, any samples based on the old SQL statement are invalidated.
Figure: Dataset With SQL Details
Actions:
Preview: Review the first few rows of the dataset.
Edit custom SQL: Edit the custom SQL that has been used to define the dataset. For more information, go to Create Dataset with SQL.
Make a copy: Create a copy of the imported dataset.
Refresh dataset: Refresh the dataset.
Actions for dataset owners:
Transfer ownership: Transfer ownership of this asset to another user. Go to Transfer Asset Ownership.
Delete dataset: Delete the dataset.
Note
This action only deletes the dataset reference that points to the file in the original data source. It does not delete the dataset in the original data source.
Warning
Deleting a dataset can't be undone.
Data Labels
Data Labels provide information about a dataset, such as its certification status, sensitivity, or data quality. Applied Data Labels appear as badges next to the dataset name on the Dataset details page.
Hover over a Data Label badge to view its category, value, description, the user who applied it, and the date it was applied. Click the badge to edit/update Data Labels.
Apply a Data Label
You must have the appropriate Data Labels capability to apply, update, or remove Data Labels.
To apply a Data Label to a dataset...
Open the Dataset details page.
Select the three-dot menu in the upper-right corner.
Select Data Labels.
Select a category, such as Certification, Sensitivity, Data Quality, or a custom category configured for your workspace.
Select the label value.
Select Save.
A confirmation message appears when the Data Label is applied. If the operation fails, an error message appears. Try the process again.
Note
A category can allow either one or multiple labels:
A radio button indicates that only one label from the category can be applied at a time. Selecting another label replaces the existing selection. Certification is a single-selection category.
A checkbox indicates that multiple labels from the category can be applied simultaneously.
Update or Remove a Data Label
To update or remove a Data Label...
Select the dataset’s three-dot menu from the dataset details page.
Select Data Labels.
Select the applicable category.
Select a different value to replace a single-selection label, or clear a selected checkbox to remove a multiple-selection label.
Select Save.
A confirmation message appears when the label is updated or removed. If the operation fails, an error message appears. Try the operation again.
Note
You can manage Data Labels from the Dataset details page or by selecting the Data Label badge or three-dot menu for a Dataset on the Dataset list page.
Asset Certification
Certification is a system-defined Data Label category that communicates whether a dataset version has been reviewed and is trusted for use. Since Certification is a single-selection category, only one certification value can be applied to a dataset version at a time.
Data Labels are version-specific. When changes create a new dataset version, the new version doesn’t inherit the labels applied to the previous version. Apply the appropriate Data Labels to the new version before treating it as certified.
For complete details, go to Data Labels and Asset Certification.
Note
Data Labels are applied, updated, or removed only on the latest version. Historical versions are read-only.
Disabled Data Labels
Workspace administrators can disable Data Labels that are no longer available. A disabled label that is already applied remains visible on the dataset, but it can’t be applied to additional datasets. If you remove a disabled label, you can’t apply it again. For more details on using Data Labels, go to Data Labels.