---
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title: Set Up a Streaming Data Transform
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/data/264-0-0/c360_a_streaming_transform_setup.md
canonical_url: https://help.salesforce.com/s/articleView?id=data.c360_a_streaming_transform_setup.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: 6c7665759b26703ec34fc23091f80477f2046c68d54f8b7985b018b350a5e909
description: When you set up a streaming data transform, it reads and processes all records in the source and writes the data to the target object. The source and target objects must be different objects.
products:
  - Data 360
release: "264"
---
# Set Up a Streaming Data Transform

When you set up a streaming data transform, it reads and processes all records in the source and writes the data to the target object. The source and target objects must be different objects.

1. In Data Cloud, on the Data Transforms tab, click **New**.
    
    If the Data Transforms tab isn’t visible, click More and select Data Transforms. If your org has already used the maximum number of transforms allowed, the New button doesn’t appear.
2. Select **Streaming Data Transform**, then click **Next**.
3. Select **Data Model Object** or **Data Lake Object**, then click **Next**. If you select Data Model Object, choose a data space from the dropdown menu.
    
    A data transform that runs on data model objects is restricted to read and write to the selected data space.
4. Enter a name for the data transform, and optionally, select a currency.
    
    This setting converts data with multiple currencies to a single value. If you have multiple data transforms that write to the same target, make sure they all have the same currency.
5. For the Target Object field, choose a DLO or DMO from the list or select **Create New**. Only DLOs and DMOs created using Create New are displayed in this list.
6. Click **Next**.
7. In the Expression field, enter a SQL statement to tell the streaming data transform which records to process and how to map the transformed output to the target object.
    
    If you chose to create a new DLO or DMO, the syntax will determine the columns and data type for the new DLO or DMO.
8. Verify your SQL statement’s syntax by clicking **Check Syntax**.
    
    If a streaming data transform contains syntax errors or validation errors, such as incorrect API names for the source and target , you can’t save it. These errors appear on the left side. Fix them before saving.
    
    ![New Streaming transform expression.](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/data_cloud/images/c360_a_streaming_transform_expression.png)
9. If you chose an existing target DLO or DMO, click **Save**.
    
    Streaming data transforms are activated immediately when saved. You can’t change a streaming data transform after saving it. If you must change a streaming data transform, delete it and create another one.
10. If you are creating a new DLO or DMO, click **Next** and you are prompted to enter a name for the DLO or DMO and the category.
    
    ![New Streaming adding fields to DMO for new transform.](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/data_cloud/images/c360_a_streaming_transform_new_DMO.png)
    
    1. (Optional) Select a value from the **Enable Value Suggestion** field.
        
        Value suggestions streamline the process by providing a list of valid values for fields.
    2. Choose a key qualifier to create fully qualified keys (FQK) and select a primary key field.
    3. Click **Save**.
        
        After the DLO or DMO is created, a streaming data transform is created that uses it as target data source. Subsequently, this transform executes to populate the DLO or DMO with data.