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Use this guide to configure the Salesforce Data360 connector. Configure and run Salesforce Data360 metadata workflows externally with YAML:

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How to Run the Connector Externally

To run the Ingestion via the UI you’ll need to use the OpenMetadata Ingestion Container, which comes shipped with custom Airflow plugins to handle the workflow deployment. If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework anywhere.

External Schedulers

Get more information about running the Ingestion Framework Externally

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Requirements

OpenMetadata connects to Salesforce Data360 through the Salesforce REST API using a connected app that authenticates with the OAuth 2.0 client credentials flow. You’ll need:
  • A Salesforce connected app configured for the OAuth 2.0 client credentials flow. The app provides the Consumer Key and Consumer Secret.
  • The Data360 (Data Cloud) API scopes — cdp_query_api and cdp_profile_api — granted to that connected app.
  • An integration user with permission to view the data spaces and objects you want to ingest: Data Lake Objects, Data Model Objects, and Calculated Insights.

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Python Requirements

Use a Python version supported by the openmetadata-ingestion package that matches your OpenMetadata server. To find the supported range for your release, check the Requires-Python metadata of that release’s ingestion package. To run the Salesforce Data360 ingestion, install:

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Metadata Ingestion

All connectors are defined as JSON Schemas. See the Salesforce Data360 connection JSON Schema for the structure used to create a connection to Salesforce Data360. To create and run a metadata ingestion workflow, create a YAML configuration. The configuration connects to the source, processes entities if needed, and reaches the OpenMetadata server. The workflow is modeled around the following JSON Schema.

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1. Define the YAML Config

This is a sample config for Salesforce Data360:

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2. Run with the CLI

First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:
Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration, you will be able to extract metadata from different sources.