> ## Documentation Index > Fetch the complete documentation index at: https://docs.narrative.io/llms.txt > Use this file to discover all available pages before exploring further. # Configuring dataset retention policies > Add, edit, and manage retention policies from the dataset details page to automate data lifecycle cleanup Retention policies automate data lifecycle management by removing data that has exceeded a specified age. You can configure retention policies directly from the dataset details page using the **Retention** tab. This guide covers the UI-based configuration. You can also manage retention policies programmatically through the [Upsert Retention Policies API](/api-reference/datasets/upsert-retention-policies-for-a-dataset) or the [TypeScript SDK](/guides/sdk/managing-datasets). ## Prerequisites * A dataset you own or have write access to * The dataset must be on an active [data plane](/concepts/primitives/data-planes) ## Understanding policy classes Before configuring a policy, choose the right policy class for your use case. The available classes depend on your data plane: | Policy class | What it deletes | Available on | | ---------------- | ---------------------------------------------------------- | --------------------- | | **Row TTL** | Individual rows whose event timestamp exceeds the interval | Snowflake data planes | | **Snapshot TTL** | Old ingestion snapshots based on snapshot age | AWS data planes | | **Table TTL** | The entire dataset when table age exceeds the interval | Both | For a detailed explanation of each policy class, see [Dataset retention policies](/concepts/primitives/dataset-retention-policies). Deletions on Snowflake-based data planes are immediate with no grace period. AWS-based data planes apply a default 30-day grace period before permanent deletion. ## Adding a retention policy Go to **My Data > Datasets** and select the dataset you want to configure. Select the **Retention** tab on the dataset details page. If no policies are configured, you see an empty state with a prompt to add your first policy. Click the **New Policy +** button. You can either: * Click the button directly to open the manual configuration drawer * Click the dropdown arrow to choose between **Ask Rosetta** (AI-assisted) or **Configure manually** In the configuration drawer, set the following: **Policy class** — Select the type of retention policy. The available options depend on your data plane. **Interval** — Choose a preset duration (30, 90, 180, or 365 days) or enter a custom [ISO 8601 duration](https://en.wikipedia.org/wiki/ISO_8601#Durations) such as `P60D` for 60 days. **Class-specific settings:** **Event time clock** — Select the [Rosetta Stone](/concepts/rosetta-stone/overview) attribute that maps to a timestamp column in your dataset. The dropdown shows all `timestamptz` attributes mapped on the dataset. If you don't specify one, the system defaults to `nio_last_modified`. **Retention value** — Choose how snapshots are handled: * **Time-based** — Delete snapshots older than the interval * **Retain everything** — Keep all snapshots indefinitely * **Expire everything** — Remove all snapshots on each evaluation **Clock type** — Choose how table age is measured: * **`created_at`** — Uses when the dataset was created * **`max_event_time`** — Uses the most recent event timestamp (requires a column reference) * **`static_time`** — Uses a fixed timestamp (requires a column reference) **Status** — Toggle the policy on or off. Policies are enabled by default. Click **Add Policy** to save. The policy appears in the retention policies table. ## Using Ask Rosetta to generate a policy Instead of configuring a policy manually, you can describe what you want in plain language and let Rosetta generate the configuration for you. From the **Retention** tab, click the dropdown arrow on the **New Policy +** button and select **Ask Rosetta**. Enter a plain-language description of the retention behavior you want. For example: > Delete individual rows older than 90 days based on when the event occurred. Use the event\_timestamp attribute as the clock. Keep the policy enabled. You can also click **Use this prompt** to start with the sample prompt provided. Click **Generate Policy**. Rosetta converts your description into a structured policy configuration and opens the configuration drawer with the values pre-filled. Review the settings and adjust if needed. Click **Add Policy** to save the generated configuration. If you prefer to configure manually instead, click the **Manual** button in the Ask Rosetta dialog to switch to the manual configuration drawer. ## Editing a retention policy To modify an existing policy, click the actions menu (three dots) on the policy row and select **Edit**. The configuration drawer opens in edit mode with the current settings pre-populated. You cannot change the policy class when editing — to switch policy classes, delete the existing policy and create a new one. ## Enabling or disabling a policy You can toggle a policy on or off without deleting it: * **From the table** — Click the toggle switch next to the policy class badge * **From the actions menu** — Click the actions menu and select **Enable** or **Disable** Disabled policies remain in the configuration but are not evaluated during retention runs. ## Deleting a retention policy Click the actions menu on the policy row and select **Delete**. Confirm the deletion in the dialog that appears. This removes the policy configuration entirely — it does not undo any deletions that have already occurred. ## Related content Understand how retention policies work and when to use each policy class Learn where your data physically resides and how it affects retention behavior Set retention on materialized views using NQL Manage retention policies programmatically