What is ETL?
ETL has its roots in the rise of central data repositories. With the dawn of data warehouses around the 1990s, tools began being made specifically focused on extracting data from siloed systems, transforming it into the destination format, and then loading it into the new destination (or ETL). Over the years, ETL has grown to become stronger and stronger with the increase in demands during the data age of marketing.
ETL tools typically do all three of the steps and are a critical part of ensuring that data is prepped completely and accurately for things such as reporting, analytics, and other data-driven actions, including machine learning. The following is a basic definition of each of the three steps in ETL: