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Activation for Data 360 Data Model Objects
Use data from various sources to build complete customer profiles by activating a data model object (DMO). This feature presents data in a readily actionable format and facilitates personalized customer experiences. Data 360 offers two methods for DMO activation: streaming and batch, with each designed for different use cases and destinations.
Required Editions
| Available in: Lightning Experience | Available in: Developer, Enterprise and Unlimited Editions |
| Feature | Streaming Activation | Batch Activation |
|---|---|---|
| Data Activated | Sends individual record changes in near realtime. | Exports the entire DMO table in batches. |
| Supported Targets | Meta Conversion API platform. | Wide range of targets, including Marketing Cloud Engagement, S3 (Legacy), Google Cloud Storage, Azure, SFTP, Data 360, and strategic partner platforms such as Google, Meta, and LinkedIn. You can also use batch DMO activation in activation-triggered flow and activate to any API-based destination configured in the flow. |
| Use Cases | Time-sensitive, event-based actions where immediate data is crucial. | Large-scale, bulk data transfers, archiving, and populating other systems. |
Streaming DMO Activation
Streaming activation is designed for near real-time use cases and sends data to a destination as events occur.
Standard and Custom Events
When creating a streaming activation, you can use either a standard or a custom event.
- Standard Events—These are predefined by the destination platform (for example, Meta CAPI). All necessary attributes and values are included automatically. This is the recommended approach for first-time users.
- Custom Events—Create custom events and add only the attributes you want to provide a more tailored activation experience.
Activation Membership Filtering with Data Graphs
When you add filters to the activation membership in a streaming DMO activation, the DMOs available for filtering depend on whether the activation uses a data graph.
- Without a data graph, only attributes from the activated DMO are available for activation membership filtering.
- When a data graph is used in the activation, you can filter on attributes from any DMO included in that data graph, up to 2 hops away from the activated DMO.
Batch DMO Activation
Use batch activation when you need to send a complete dataset for analysis, archiving, or large-scale marketing campaigns. Common scenarios include:
- Exporting a full customer profile table to a data warehouse for business intelligence.
- Sending a large, comprehensive list of product recommendations or personalized attributes to Marketing Cloud Engagement.
- Archiving a complete snapshot of a DMO to a secure SFTP location for compliance or record-keeping.
Considerations
- You can activate external DMOs if they are accelerated. In Bring Your Own Lake (BYOL) scenarios, only accelerated DMOs are supported. Non-accelerated external DMOs are not supported.
- Batch DMO activation supports Profile, Engagement, and Other DMO types. You can’t use it for Audience DMOs and certain system-generated DMOs.
- Unlike batch segment activations, there’s currently no option to set a custom schedule for Batch DMO activations in the UI.
- When activating an Engagement DMO, the activation payload includes records only from the last 90 days. It doesn’t send the entire history of engagement records.
- Create an Activation for a DMO Using a Standard Event
When you create an activation in Data Cloud using a standard event, the required attributes from the data model object (DMO ) are automatically added. Activating DMOS is supported by the Meta Conversion API platform. - Create an Activation for a DMO Using a Custom Event
When you create a DMO activation in Data 360 using a custom event, add the required attributes for a tailored activation experience. DMO Activations are supported by the Meta Conversion API platform. - Create a Batch DMO Activation in Data 360
Create a batch DMO activation to export an entire data model object (DMO). Learn how to configure your activation by filtering records, adding additional attributes, and ranking the audience before publishing.
