More actions
You can Delete or Enable a dataset for Profile from the Dataset details view. To see the available actions, select … More in the top right of the UI. The drop-down menu appears.
If you select Enable a dataset for Profile, a confirmation dialog appears. Select Enable to confirm your choice.
If you select Delete, the Delete dataset confirmation dialog appears. Select Delete to confirm your choice.
You can also delete a dataset or add a dataset for use with Real-Time Customer Profile from the inline actions found on the Browse tab. See the inline actions section for more information.
Inline dataset actions
The datasets UI now offers a collections of inline actions for each available dataset. Select the ellipsis (…) of a dataset that you want to manage to see the available options in a pop-up menu. The available actions include;
More information on these available actions can be found in their respective sections. To learn how to manage large numbers of datasets simultaneously, refer to the bulk actions section.
Preview a dataset
You can preview dataset sample data from both the inline options of the Browse tab and also the Dataset activity view. From the Browse tab, select the ellipses (…) next to the dataset name you wish to preview. A menu list of options appears. Next, select Preview dataset from the list of available options. If the dataset is empty, the preview link is deactivated and instead indicates that the preview is not available.
This opens the preview window, where the hierarchical view of the schema for the dataset is shown on the right.
Alternatively, from the Dataset activity screen, select Preview dataset near the top-right corner of your screen to preview up to 100 rows of data.
For more robust methods to access your data, Experience Platform provides downstream services such as Query Service and JupyterLab to explore and analyze data. See the following documents for more information:
Manage and enforce data governance on a dataset
You can manage the data governance labels for a dataset by selecting the inline options of the Browse tab. Select the ellipses (…) next to the dataset name that you wish to manage, followed by Manage data and access labels from the dropdown menu.
Data usage labels, applied at the schema level, allow you to categorize datasets and fields according to usage policies that apply to that data. See the Data Governance overview to learn more about labels, or refer to the data usage labels user guide for instructions on how to apply labels to schemas for propagation to datasets.
Enable a dataset for Real-Time Customer Profile
Every dataset has the ability to enrich customer profiles with its ingested data. To do so, the schema that the dataset adheres to must be compatible for use in Real-Time Customer Profile. A compatible schema satisfies the following requirements:
- The schema has at least one attribute specified as an identity property.
- The schema has an identity property defined as the primary identity.
For more information on enabling a schema for Profile, see the Schema Editor user guide.
You can enable a dataset for Profile from both the inline options of the Browse tab and also the Dataset activity view. From the Browse tab of the Datasets workspace, select the ellipsis of a dataset that you want to enable for Profile. A menu list of options appears. Next, select Enable unified profile from the list of available options.
Alternatively, from the dataset’s Dataset activity screen, select the Profile toggle within the Properties column. Once enabled, data that is ingested into the dataset will also be used to populate customer profiles.
Datasets that have been enabled for Profile can also be filtered on this criteria. See the section on how to filter Profile enabled datasets for more information.
Manage dataset tags
Add custom created tags to organize datasets and improve search, filtering, and sorting capabilities. From the Browse tab of the Datasets workspace, select the ellipsis of a dataset that you want to manage followed by Manage tags from the dropdown menu.
The Manage tags dialog appears. Enter a short description to create a custom tag, or choose from a pre-existing tag to label your dataset. Select Save to confirm your settings.
The Manage tags dialog can also remove existing tags from a dataset. Simply select the ‘x’ next to the tag that you wish to remove and select Save.
Once a tag has been added to a dataset, the datasets can be filtered based on the corresponding tag. See the section on how to filter datasets by tags for more information.
For more information on how to classify business objects for easier discovery and categorization, see the guide on managing metadata taxonomies. This guide explains how users with the right permissions can create pre-defined tags, assign them to categories, and manage all related CRUD operations in the Experience Platform UI.
(Beta) Set data retention policy
Manage dataset expiration and retention settings using the inline action menu from the Browse tab of the Datasets workspace. You can use this feature to configure how long data is retained in the data lake and Profile store. The expiration date is based on when data was ingested into Experience Platform and your configured retention period.
To configure your retention period, select the ellipsis next to the dataset followed by Set data retention policy from the dropdown menu.
The Set dataset retention dialog appears. The dialog displays sandbox-level license usage metrics, dataset-level details, and current data retention settings. These metrics show your usage compared to your entitlements and help you assess dataset-specific storage and retention configurations. The metrics include dataset name, type, Profile enablement status, and data lake and Profile store usage.
Configure your preferred retention period in the data retention settings dialog. Enter a number and select a time unit (days, months, or years) from the dropdown menu. You can configure separate retention settings for the data lake and Profile Service.
To support transparency and monitoring, timestamps are provided for the last and next data retention job executions. The timestamps help you understand when the last data cleanup occurred and when the next one is scheduled.
Storage impact insights
To open a visual forecast of the storage impact of different retention policies, select View Experience Event Data distribution.
The chart displays the distribution of experience events across various retention periods for the currently selected dataset. Hover over each bar to see the precise number of records that will be removed if the selected retention period is applied.
You can use the visual forecast to evaluate the impact of different retention periods and make informed business decisions. For example, if you select a 30-day retention period and the chart shows that 60% of your data will be deleted, you may choose to extend retention to preserve more data for analysis.
When you are satisfied with your configuration, select Save to confirm your settings.
After configuring your retention settings, use the Monitoring UI to confirm that your changes were executed by the system. The Monitoring UI provides a centralized view of data retention activity across all datasets. From there, you can track job execution, review how much data was deleted, and ensure that your retention policies are functioning as expected. This visibility supports governance, compliance, and efficient data lifecycle management.
To learn how to use the monitoring dashboard to track source dataflows in the Experience Platform UI, see the Monitor dataflows for sources in the UI documentation.
For more information on the rules that define dataset expirations date ranges and best practices for configuring your data retention policy, see the frequently asked questions page.