> For the complete documentation index, see [llms.txt](https://docs.primeur.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.primeur.com/panorama-2.0.1/operational-resilience/business-continuity-playbook/data-watcher-synchronization.md).

# Data Watcher synchronization

Each critical flow in Panorama is composed of different sets of information, which follow distinct data ownership models and determine how the information is managed and updated.

**Data Watcher–managed data**

Some fields are defined and maintained in **Data Watcher**, as part of the original model. For example cut-off times and other technical attributes defined in the model. 

If these values are updated in Data Watcher, Panorama does not automatically reflect the changes. To keep the data aligned, you must manually synchronize the critical flow.

To update **Data Watcher–managed** fields, use the contextual menu available for each flow. From the **three-dot menu** select **Data Watcher sync**. This action refreshes the critical flow with the latest data coming from Data Watcher, ensuring consistency after any changes in the original model.

See the [Data Watcher synchronization](/panorama-2.0.1/operational-resilience/business-continuity-playbook/data-watcher-synchronization.md) page for details. 

**Panorama-managed data**

Other information is managed directly within Panorama, such as business information, criticality level and contingency procedures. 

This data is **owned by Panorama** and is not shared back with Data Watcher.

## Synchronization behavior

Panorama does **not automatically update** Data Watcher–managed fields when changes occur in Data Watcher.

To align the data open the three-dot menu of a critical flow and select **Data Watcher sync**.

The synchronization process runs in the background. 

{% hint style="info" %}
Note that **no confirmation message or visible changes appear in the UI.**
{% endhint %}

The flow is updated with the latest technical data coming from Data Watcher. Updated values are stored internally and used in subsequent exports. 

The effects of synchronization become visible when exporting the playbook. For example, if a **cut-off time is added or updated in Data Watcher**, after performing a sync (or during the next automatic export), the new value will appear in the exported file.