All data is created in one place and moved–sometimes very often–from one storehouse to another. ETL (extract, transform and load) and data integration have always been among the thorniest problems in all of IT to solve efficiently. This software aids in copying or moving data from one database or repository to another and ensuring that the data is formatted correctly for the task at hand. ETL enables putting data to work and maximizing its value.
Generally, the ETL process has worked well, and it has been improved over time. Today, ETL, along with its brother Extract, Load, Transform (ELT), is used within increasingly complex data frameworks, including edge computing, the internet of things, connected supply chains, cloud environments and others. As enterprises move to more advanced business intelligence and data analytics including systems that rely on machine learning and artificial intelligence (AI), ETL functionality is crucial.