What is ETL ?

ETL: Extract, Transform, Load

In data engineering, the term ETL refers to the process of extracting data from various sources, transforming that data into a format that is suitable for analysis, and then loading the transformed data into a destination, such as a data warehouse or database.

The ETL process is a critical part of many data engineering pipelines, as it allows data to be extracted from a variety of sources, cleaned and transformed to remove errors and inconsistencies, and then loaded into a destination where it can be easily accessed and analyzed.

The ETL process typically involves three main steps:

  1. Extract: Data is extracted from one or more sources, such as databases, files, or APIs.
  2. Transform: The extracted data is cleaned and transformed to remove errors and inconsistencies, and to make it more suitable for analysis. This may involve operations such as filtering, sorting, or aggregating the data.
  3. Load: The transformed data is loaded into a destination, such as a data warehouse or database, where it can be easily accessed and analyzed.

Overall, the ETL process is an important part of data engineering, as it allows data to be extracted from various sources, cleaned and transformed, and then loaded into a destination for analysis.


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