FME Workflows

30 minutes

Learning Objectives

After completing this unit, you will be able to:

  • Understand how data flows through a workspace.
  • Create a workspace with multiple formats.
  • Create a workspace with multiple feature types.
  • Employ basic best practice techniques (bookmarks and annotations) in building your workspaces.


A basic workspace in FME reads in data in one format, transforms it, and writes it out, optionally in a different format.

However, there are multiple other methods for constructing more advanced workspaces and for directing the flow of data through a workspace in unique ways.

Some example uses for these techniques might be:

  • To branch your data into multiple streams
  • To design large-scale workspaces a small section at a time
  • To read data from multiple formats within a single workspace
  • To carry out actions after a dataset is written
  • To use data stored on web services
  • To test run individual parts of a workspace

In this unit we will cover some of these different FME workflows, illustrating the flexibility of FME for data transformation.

results matching ""

    No results matching ""