Option A is correct because Lakeflow Connect provides a built-in, fully managed Salesforce connector. It ingests Salesforce data into Databricks, supports incremental processing, and publishes governed destination tables in Unity Catalog. Managed SaaS connectors handle source-specific authentication, incremental reads, schema evolution, and automated retries, reducing the custom engineering required for API pagination, state tracking, and failure recovery. Calling the Salesforce REST API from a notebook would require the team to develop and maintain those capabilities itself. Auto Loader is designed to discover and incrementally process files arriving in cloud object storage; it does not connect directly to Salesforce. Using an exported Amazon S3 path would also require a separate export system outside the requested managed Databricks ingestion experience. Therefore, option A is the low-code capability that directly satisfies the Salesforce ingestion requirement.
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