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:
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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