ETL, which stands for Extract, Transform, Load, is a process used in data integration to extract data from multiple sources, transform it to fit the target system's format, and then load it into the target system.

The Extract phase involves gathering data from various sources such as databases, flat files, and APIs. In the Transform phase, the extracted data is cleaned, validated, and formatted to match the target system's schema. This phase may also involve enriching the data by adding additional information or calculations. Finally, in the Load phase, the transformed data is loaded into the target system, which could be a data warehouse, database, or another application.

ETL is a critical process in data integration, as it enables businesses to consolidate data from various sources and create a unified view of their data. This helps in making informed decisions, gaining insights, and enhancing business performance. ETL is commonly used in various industries such as finance, healthcare, retail, and manufacturing.

In conclusion, ETL is a data integration process that involves extracting data from multiple sources, transforming it to fit the target system's format, and loading it into the target system. This process is crucial for businesses to consolidate their data and gain a holistic view of their operations.