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DP-750 · 3.1.2 · Prepare and process data

Choose ingestion tool

Choose an appropriate data ingestion tool, including Lakeflow Connect, notebooks, and Azure Data Factory

Select managed connectors, notebooks, or external orchestration based on source support and control requirements.

Start with the most managed option

Microsoft Learn Lakeflow Connect database connector architecture from source through connection, gateway, staging, pipeline, and destination.

Lakeflow Connect handles source connectivity, incremental ingestion, staging, and destination tables for supported enterprise sources.

Choose by support and control

  • Supported SaaS or database sourceLakeflow Connect
  • Custom API or protocol logic is requiredNotebook
  • Workflow spans multiple Azure servicesAzure Data Factory
Ingestion tool

Managed connectors reduce custom operational code. Notebooks maximize flexibility. Data Factory is useful when Databricks is one step in a larger Azure orchestration.

Drop down only when needed

Use the highest-level tool that still gives enough control. Familiarity alone is not a reason to build and maintain a custom connector.

Key points

  • Lakeflow Connect: Managed ingestion for supported enterprise sources
  • Notebook: Flexible custom code and specialized APIs
  • Data Factory: External orchestration across Azure services
  • Tradeoff: Managed tools reduce custom operational code

Exam trap

Do not build a custom notebook connector when a managed connector already meets the requirement.

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Checked on October 4, 2026. Report a problem

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