Which scenario would be appropriate for using a dynamic workflow?

• A. You need to build a workspace that converts any spatial data inputs, regardless of attributes, to GML.
• B. You need to build a workspace that loads as-built CAD drawings with a predictable schema into a GIS database.
• C. You need to build a workspace that takes data with a set schema but no set format and writes it out to the user's choice of format.
• D. You need to build a workspace that uploads monthly expense reports in Excel format to a database. The schema doesn't change month-to-month.

Answer: (A)

Dynamic workflows let a single workspace adapt to varying input datasets, handling different formats, schemas, and attribute sets on the fly and still produce a consistent output. This flexibility is perfect when you need to convert any spatial data inputs, regardless of their attributes, into a single target format like GML. The workspace can read a wide range of sources, map what it encounters to the GML structure, and manage differences without requiring separate branches for each dataset.

If the data you’re working with have a predictable schema, a static workflow is more straightforward because you can define exact field mappings and processes once and reuse them without the overhead of dynamic adaptation. Scenarios where the input format is fixed month to month or where the schema doesn’t change don’t benefit as much from dynamic behavior. Similarly, when you want to output to multiple formats but the input schema is known, you can often configure writers accordingly without needing a fully dynamic read path.