Advanced Data Lifecycle Management in Adobe Experience Platform

Manage the data you retain in Adobe Experience Platform so that it continues to support your active use cases, retention requirements, and licensing entitlements. As your data volumes grow, use retention and deletion controls to remove data that is no longer needed and keep storage aligned with how the data is used.

This overview introduces the available options and explains when to use each one, including targeted deletion, dataset expiration, and ongoing retention policies.

Data Lifecycle Management and Privacy Service privacy-service

Use Advanced Data Lifecycle Management when you need to manage data retention or remove data for operational purposes, such as data cleansing, data minimization, or managing stored data over time.

For privacy or regulatory data-subject rights requests, use Adobe Experience Platform Privacy Service instead. Do not use record delete or other Data Lifecycle Management capabilities to fulfill these requests.

Understand retention across Experience Platform retention-across-platform

To choose an appropriate retention policy, first consider where your data is stored and how you use it. The Profile store supports engagement workflows such as segmentation, activation, and personalization, while the data lake supports analytical and longer-term use cases. A dataset can support either type of workflow or both.

For Experience Event data stored in both repositories, manage retention in each repository independently. Expiring data under one retention policy does not automatically cause the same data to expire under the other. Both Profile store and data lake storage are subject to your organization’s licensing entitlements.

Data retention and deletion options capabilities

Choose a capability based on what you need to remove and where the data is stored.

Use record delete or dataset expiration for one-time removal actions. To manage data automatically over time, use Experience Event expiration, a data lake retention policy, or Pseudonymous Profile data expiration.

Choose or implement a capability choose-or-implement

For more detailed help choosing the right capability, see Choose the right data lifecycle management capability. It compares the available retention and deletion options, explains their scope, and helps you determine when to use each one.

If you already know which capability you need, continue to the implementation guidance below.

Implement a data lifecycle task implement

Use the task-specific guidance below to navigate to the relevant implementation documentation.

Remove specific records

To remove records associated with a primary identity, use record delete in the Data Lifecycle workspace or submit a request with the work order API.

Remove an entire dataset

To remove an entire dataset on a scheduled date, use dataset expiration in the Data Lifecycle workspace or the dataset expiration API.

Configure Experience Event retention

To control how long Experience Events remain in the Profile store or data lake, use the Set data retention policy workflow in the Datasets workspace. In this workflow, the Profile Service retention policy configures Experience Event expiration in the Profile store, while a data lake retention policy applies row-level expiration in the data lake. Configure each retention policy independently based on how long you need the data in each repository.

Remove inactive pseudonymous profiles

To remove inactive pseudonymous profiles, configure Pseudonymous Profile data expiration in Profile settings. This setting applies at the sandbox level and is separate from the dataset-level retention settings used for Experience Events.

Timelines and transparency timelines-and-transparency

Record delete requests and dataset expiration do not complete immediately. A scheduled dataset expiration remains pending until its expiration time, after which processing begins. You can monitor the current status of these operations at key processing milestones.

For detailed processing stages and timing, including applicable SLA information for record delete requests, see Data Lifecycle processing timelines.

Additional guidance additional-guidance

Use the following resources when you need supporting information beyond the task-specific guidance above: