{"componentChunkName":"component---src-templates-markdown-template-jsx","path":"/guides/data-warehouse/composable-audiences/data-models/generic-data-models/","result":{"data":{"pageMetadata":{"title":"Create a Generic Data Model","path":"/guides/data-warehouse/composable-audiences/data-models/generic-data-models/","sourceCode":null,"metadataParent":{"title":"Data Models","path":"/guides/data-warehouse/composable-audiences/data-models/","sourceCode":null,"hasVersionPicker":null,"metadataChildren":[{"title":"Data Models Overview","path":"/guides/data-warehouse/composable-audiences/data-models/overview/","order":1,"label":null},{"title":"Create a User Data Model","path":"/guides/data-warehouse/composable-audiences/data-models/user-data-models/","order":2,"label":null},{"title":"Create an Event Data Model","path":"/guides/data-warehouse/composable-audiences/data-models/event-data-models/","order":3,"label":null},{"title":"Create a Generic Data Model","path":"/guides/data-warehouse/composable-audiences/data-models/generic-data-models/","order":4,"label":null}],"metadataParent":{"title":"Composable Audiences","path":"/guides/data-warehouse/composable-audiences/","metadataChildren":[{"title":"Warehouse Setup Overview","path":"/guides/data-warehouse/composable-audiences/overview/","order":0.5,"label":null},{"title":"Connections","path":"/guides/data-warehouse/composable-audiences/connections/","order":1,"label":null},{"title":"Data Models","path":"/guides/data-warehouse/composable-audiences/data-models/","order":2,"label":null}],"metadataParent":{"title":"Data Warehouse","path":"/guides/data-warehouse/","metadataChildren":[{"title":"Composable Audiences","path":"/guides/data-warehouse/composable-audiences/","order":1,"label":null},{"title":"Warehouse Sync","path":"/guides/data-warehouse/warehouse-sync/","order":4,"label":null}],"metadataParent":{"title":"Guides","path":"/guides/","metadataChildren":[{"title":"Platform Overview","path":"/guides/platform-overview/","order":0.5,"label":null},{"title":"Getting Started","path":"/guides/getting-started/","order":1,"label":null},{"title":"mParticle Agent","path":"/guides/mparticle-agent/","order":1.5,"label":null},{"title":"Oversight","path":"/guides/oversight/","order":2,"label":null},{"title":"Data Platform","path":"/guides/data-platform/","order":3,"label":null},{"title":"Data Warehouse","path":"/guides/data-warehouse/","order":4,"label":null},{"title":"Customer 360","path":"/guides/customer-360/","order":5,"label":null},{"title":"Analytics","path":"/guides/analytics/","order":6,"label":null},{"title":"Audiences","path":"/guides/audiences/","order":7,"label":null},{"title":"Settings","path":"/guides/settings/","order":8,"label":null},{"title":"Troubleshooting mParticle","path":"/guides/troubleshooting/","order":10,"label":null},{"title":"Default Service Limits","path":"/guides/default-service-limits/","order":11,"label":null},{"title":"Glossary","path":"/guides/glossary/","order":12,"label":null}],"metadataParent":null}}}}},"markdownRemark":{"html":"

Generic Data Models are a flexible option for data that does not neatly fit into user or event categories. These models often include contextual or supplemental attributes such as subscription plans, device types, or account-level metadata. Like other models, generic data models are defined using SQL and must be linked to a User Data Model.

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\n \n \n \n \n \n \n \n Example

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Here is a simple SQL query you might use to define a generic data model for subscription plans:

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SELECT\n  user_id,\n  subscription_id,\n  plan_tier,\n  renewal_date,\n  auto_renew\nFROM ecommerce.subscriptions
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With this model in place, you could build an audience such as “users on the Premium plan whose renewal date is within the next 30 days but who have auto-renew turned off.”

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This example focuses on context about the user. When combined with a User Data Model (who the user is) and an Event Data Model (what the user does), you can target audiences with profile, behavior, and subscription context together.

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\n \n \n \n \n \n \n \n To create a generic data model

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\n \n \n \n \n \n \n \n 1. Enter your query

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    \n
  1. Navigate to Data Warehouse > Data Models using the left-hand navigation.
    2. \n
  2. Click + Add Data Model in the upper right corner.
    3. \n
  3. Select Generic Data Model.
    4. \n
  4. Select a warehouse connection using the Data Connection dropdown menu.
    5. \n
  5. \n

    Under SQL Query, enter the SQL query you want to execute against your warehouse. Use joins, filters, grouping, and case statements as needed.

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    6. \n
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    \n
  1. Click Run Query.
    2. \n
  2. Click Next Step to continue.
    3. \n
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\n \n \n \n \n \n \n \n 2. Enter your configuration details

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    \n
  1. Enter a descriptive name for your data model.
    2. \n
  2. Select a primary ID column retrieved from your SQL query to uniquely identify each record.
    3. \n
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    \n
  1. Click Save Data Model to continue.
    2. \n
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\n \n \n \n \n \n \n \n 3. Enter your column settings (optional)

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    \n
  1. Use the Enabled toggle to disable or re-enable a column.
    2. \n
  2. Review the data type mParticle detects for each column. Update if needed.
    3. \n
  3. Enable Autocomplete to see cached values for up to 7 days when building audiences.
    4. \n
  4. Use the Is Case Sensitive (Yes/No) setting to control casing for autocomplete.
    5. \n
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Click Save Data Model to continue.

\n","frontmatter":{"title":"Create a Generic Data Model","order":4,"seoTitle":null,"seoDescription":null},"parent":{"__typename":"File","modifiedTime":"October 12, 2026"}}},"pageContext":{"slug":"/guides/data-warehouse/composable-audiences/data-models/generic-data-models/"}},"staticQueryHashes":["2950460867"]}