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.
• Use partial runs to debug your workspace.
• Employ basic best practice techniques (bookmarks and annotations) in building your workspaces.

Workflows

A basic workspace in FME is constructed and laid out strictly to the concept of ETL: Extract-Transform-Load.

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.