Extract, Transform, Load (ETL) is a process used to collect, clean, and move data from various sources into a target system, such as a data warehouse or data lake. The process is typically broken down into three distinct steps:
Extract: Data is collected from various sources, such as databases, files, or APIs.
Transform: The extracted data is then cleaned, transformed, and prepared for loading into the target system. This step involves tasks such as data mapping, data validation, and data cleansing.
Load: The transformed data is then loaded into the target system, where it can be used for analysis, reporting, and decision-making.
ETL is a crucial process in data warehousing and business intelligence as it enables organizations to make sense of large and complex datasets. The use of ETL process also helps to ensure data quality and consistency by removing duplicate, incomplete, and inaccurate data and standardizing the data into a format that can be easily analyzed.