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DP-600 · 2.1.3 · Prepare data

Ingest or access data

Ingest or access data as needed

Choose , , pipeline, dataflow, , or based on copying, freshness, transformation, and streaming needs.

The core idea

Six Fabric data access and ingestion choices: shortcut, mirroring, pipeline Copy activity, Dataflow Gen2, notebook, and Eventstream, each with its best-fit use case.

Start with three questions: must the data be copied, how fresh must it be, and how much transformation is required?

reference open-format data in place. keeps a database or catalog synchronized into Fabric. Pipelines move data on a schedule or trigger.

Use for visual Power Query transformations, for custom Spark logic, and for continuous event ingestion.

Key points

  • : access open-format data without copying
  • : continuously sync an operational database
  • Pipeline: scheduled or triggered movement at scale
  • Transform: for low-code, for custom logic

Click an underlined term for a one-line explanation, or see them all in the glossary .

Exam trap

Do not copy data by default. A or option can be better when duplication, latency, or maintenance should be minimized.

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