Which method should be used for a one-time copy of a small local file into the lakehouse when you want to minimize setup?

• A. Dataflow Gen2 query
• B. Spark notebook
• C. Local file upload by using Lakehouse explorer
• D. Pipeline with the Copy data activity

Answer: (C)

For a one-time, small local file, the fastest way to get it into the lakehouse with minimal setup is to upload it directly using Lakehouse explorer. This built-in UI lets you drag in or browse to your local file and place it into the lakehouse storage (often into a specific folder or dataset) without creating pipelines, notebooks, or data flows. Once uploaded, you can query or use the data right away, which is ideal for quick ad hoc loads.

The other options require more setup. A Dataflow Gen2 query involves creating a dataflow with connections and processing steps. A Spark notebook needs you to write and run code to read the file and write it to the lakehouse. A pipeline with the Copy data activity requires building a pipeline, defining sources and sinks, and configuring executions. For a simple, one-off upload, Lakehouse explorer keeps things straightforward and fast.