In the extract, transform, and load (ETL) process, what happens during the "transform" step?

During the "transform" step of the extract, transform, and load (ETL) process, the primary function is to prepare the extracted data for analysis by processing and altering it to fit the needs of the target system. This includes normalizing and structuring the data, which helps to ensure consistency and integrity across the dataset. In this step, various operations such as cleansing, aggregating, and enriching the data are also performed. By normalizing the data, it is ensured that it adheres to a defined structure, allowing for easier analysis and reporting in the subsequent loading phase.

Transforming data is crucial as it minimizes issues related to data quality and integrity that can arise when working with raw data. The "transform" step ensures that the data is compatible with the final database or data warehouse schema and that it can be effectively utilized by end users for decision-making purposes.