ETL moves data from one or more sources to a destination like a database, data warehouse, data store, or data lake in three distinct steps. Many organizations regularly perform ETL to keep their data warehouse updated with the latest data.

Cloud ETL, also known as modern ETL, extracts both structured and unstructured data from any data source type whether they are in on-premises or cloud data warehouses, then consolidates and transforms that data and loads it into a centralized location where it can be accessed on-demand.

Cloud ETL is often used to make data readily available for analysts, engineers, and decision-makers across a variety of use cases within an organization.

Here are some of the salient advantages of using ETL for Business Intelligence, AI, and Machine Learning. ETL can help in obtaining: