What does ETL stand for in data processing?

The term ETL stands for Extract, Transform, Load, which is a fundamental process in data warehousing and analytics. This process involves three distinct steps:

1. Extract: In this initial stage, data is collected or extracted from various sources. These sources could include databases, CRM systems, flat files, APIs, and other data repositories. The extraction process aims to pull the relevant data needed for analysis or reporting, often consolidating information from disparate systems.

2. Transform: Once the data is extracted, it often needs to be cleaned and transformed to fit the structure and requirements of the target data storage system. This can include a variety of processes, such as data cleansing (removing inaccuracies), normalization (converting data into a common format), aggregation (summarizing data), and enrichment (adding additional information). The transformation ensures that the data is in the right format and quality for analysis.

3. Load: The final step in the ETL process involves loading the transformed data into a destination, typically a data warehouse or a data lake. This makes the data accessible for analysis, reporting, and visualization tools, allowing organizations to derive insights from the consolidated information.

The other options presented do not accurately represent the widely accepted definition of ET