In this chapter, we talk about the basic building blocks of any analytical setup: data, and where it sits.
If you have data from many source systems, it is important to consolidate them into a central place. In this section, we talk about the process and tooling around it.
Learn about data warehouse, the central place to store and process all your data. Understand why (and when) it's important to have a data warehouse, as well as how to choose a data warehouse.
Learn more about the common terms ETL (Extract Transform Load) and ELT (Extract Load Transform) in doing analytics. Learn why we're advocating for ELT over ETL in our book.
Learn how to turn raw data into clean, reliable and reusable data components, but within the ELT paradigm