LinkedIn Ads connector
This feature is in Beta. Workspace admins can control access to this feature from the Previews page by opting into the Lakeflow Connect for LinkedIn Ads preview. See Manage Databricks previews.
The managed LinkedIn Ads connector in Lakeflow Connect allows you to ingest advertising data from LinkedIn Ads into Databricks.
Feature availability
Feature | Availability |
|---|---|
UI-based pipeline authoring |
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API-based pipeline authoring |
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Declarative Automation Bundles |
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Incremental ingestion |
The six prebuilt report tables support incremental ingestion. The five entity tables are fully refreshed on each update. |
Unity Catalog governance |
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Lakeflow Jobs |
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SCD type 2 |
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Column selection and deselection |
You can select specific tables. |
API-based row filtering |
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Automated schema evolution: New and deleted columns |
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Automated schema evolution: Data type changes |
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Automated schema evolution: Column renames |
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Automated schema evolution: New tables | N/A |
Authentication methods
Authentication method | Availability |
|---|---|
OAuth U2M |
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OAuth M2M |
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OAuth (manual refresh token) |
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Basic authentication (username/password) |
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Basic authentication (API key) |
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Basic authentication (service account JSON key) |
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What to know before you start
Topic | Why it matters |
|---|---|
The workflow depends on your Databricks user persona:
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The steps to create a connection depend on the authentication method you choose. | |
The steps to create a pipeline depend on the interface. | |
The pipeline schedule depends on your latency and cost requirements. | |
Depending on your ingestion needs, the pipeline might use configurations like column selection. Supported configurations vary by connector. See Feature availability. |
Start ingesting from LinkedIn Ads
The following table provides an overview of the end-to-end LinkedIn Ads ingestion flow, based on user type:
User | Steps |
|---|---|
Admin |
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Non-admin | Use any supported interface to create a pipeline from an existing connection. See Ingest data from LinkedIn Ads. |