Summary
This chapter provided a practical walkthrough of what it is like to be presented with a data movement problem, and the types of questions to ask as you identify which tools and resources are most suitable for your environment and your desired source data structure.
The development of an ETL workflow for SafeGuard emphasized the value of refactoring your code to become more modular, and therefore, more maintainable long-term.
In the next chapter, we will explore powerful ETL modules in Python that we can use to enhance data pipelines, and how leveraging Python modules can make our pipelines more ubiquitous for different processes. See you in Chapter 8!
