Summary

In this chapter, we introduced the premise of ETL pipeline data loading activities, as well as some of the contingencies of designing these activities correctly. We walked through the essential steps of setting up data storage destinations and structuring schemas in anticipation of the resultant data from our pipeline. We also introduced a blend of Python capabilities to fully or incrementally load data using SQLite. Lastly, we set up our local environment with PostgreSQL, which we will use as our data loading output location for the remainder of this book. In the next chapter, we will guide you through the entire process of creating a fully operational data pipeline.