What does ETL stand for in data processing?

ETL stands for Extract, Transform, Load, which is a crucial process in data integration and data warehousing. In the ETL process, data is first extracted from various source systems, which can include databases, APIs, or flat files. Once extracted, the data undergoes transformation, where it is cleaned, standardized, and organized to suit the needs of analysis or reporting. This transformation process ensures that the data is consistent and accurate, allowing for better insights and decision-making. Finally, the transformed data is loaded into a target database or data warehouse, making it accessible for end-users and applications.

Understanding ETL is essential in the field of data science and analytics, as it enables the efficient management and preparation of large datasets for analysis. This process is foundational in creating reliable datasets that drive business intelligence and analytics efforts.