---
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title: Streaming Data Transform Use Cases
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locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/data/264-0-0/c360_a_streaming_transform_use_cases.md
canonical_url: https://help.salesforce.com/s/articleView?id=data.c360_a_streaming_transform_use_cases.htm&release=264.0.0&type=5
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description: These use cases show how you can use streaming data transforms to normalize your data, filter it, and better align it with the Data Cloud data model.
products:
  - Data 360
release: "264"
---
# Streaming Data Transform Use Cases

These use cases show how you can use streaming data transforms to normalize your data, filter it, and better align it with the Data Cloud data model.

- **[Normalize Data with UNION Use Case](https://help.salesforce.com/s/articleView?id=data.c360_a_streaming_transform_normalization.htm&release=264.0.0&type=5)**  
    Normalize data ingested into Data 360 with streaming data transforms.
- **[Merge Multiple Data Streams Use Case](https://help.salesforce.com/s/articleView?id=data.c360_a_streaming_transform_merge.htm&release=264.0.0&type=5)**  
    The Marketing Cloud Engagement connector in Data 360 uses two profile data streams to ingest data from Marketing Cloud Engagement. Both data streams include the same set of primary keys. When these data streams are mapped directly to the Individual data model object (DMO), duplicate records appear in the DMO. To solve this problem, merge the data streams into one data lake object (DLO) before mapping to the Data 360 data model.
- **[Split a Data Stream Use Case](https://help.salesforce.com/s/articleView?id=data.c360_a_streaming_transform_split.htm&release=264.0.0&type=5)**  
    A data stream containing guest checkout information includes profile and engagement data. Split the data so that it can be mapped into separate data lake objects (DLOs), one for profile information and one for engagement.