What does ETL stand for in data processing?

ETL stands for Extract, Transform, Load, which is a crucial process in data warehousing and data integration. This process involves three main stages:

1. Extract: In this stage, data is collected from various sources, which could include databases, flat files, cloud services, and other data repositories. The goal is to gather the relevant data that needs to be processed.

2. Transform: After extraction, the data undergoes various transformations to meet specific requirements and to ensure consistency. This can include cleaning the data to remove duplicates or errors, formatting it to fit into a target schema, and aggregating or summarizing data to derive valuable insights. The transformation stage is essential for improving data quality and making the data suitable for analysis.

3. Load: Finally, the transformed data is loaded into a target data store, such as a data warehouse or a database, where it can be accessed and analyzed by users and applications.

This three-step process enables organizations to consolidate their data, streamline their data analytics, and ultimately make more informed decisions based on accurate and processed information. Other choices do not accurately reflect the foundational components of the ETL process, as they either misrepresent the stages or use incorrect terminology, thus highlighting the