It’s a vitally important step to help reinforce data integrity. Tools for ETL aid in automating the extraction process and saving the considerable time (not to mention risk of human error) in performing the task manually. Additionally, many organisations are constantly undergoing digital transformation, moving away from legacy systems to newer storage options, meaning that there is no constant ‘perfect’ state of data storage for any enterprise. This is usually because source systems, lakes and warehouses are not designed to perform analytics or computational analysis in situ.
Pretty much any repository or system that an organisation uses to store data will need to have that data extracted as part of an ETL process.
As its name suggests, ETL is made up of three distinct phases: