In which of these scenarios must you use a dataset fanout?

• A. Automatically email the results of your workspace to a colleague after it runs.
• B. Create a zipped file containing multiple Excel workbooks.
• C. You want to append features to a table in a database.
• D. You want to send a JSON payload to an API using a POST request.

Answer: (B)

Dataset fanout is used when you need to split one input dataset into multiple output datasets or files. That’s exactly what you’d do if you want to end up with several Excel workbooks from a single data source, and then zip them into one archive. Each workbook would be produced by a separate writer path, driven by the fanout, rather than a single file.

The other scenarios only require one destination output: emailing results sends one set of results to a colleague, appending features to a database writes to one database table, and posting a JSON payload goes to one API endpoint. None of these need multiple outputs from the same input, so dataset fanout isn’t necessary there.