Aug. 22, 2023, 3:07 a.m. | WanjohiChristopher

DEV Community dev.to




Introduction:


When it comes to processing data for analytical purposes, ETL (Extraction, Transformation, Load) and ELT (Extract, Load, Transform) pipelines play a pivotal role. In this article, we will delve into the definitions of these two processes, explore their respective use cases, and provide recommendations on which to employ based on different scenarios.





Defining ETL and ELT:


ETL, which stands for Extraction, Transformation, and Load, involves the extraction of data from various sources, transforming it to meet specific requirements, and …

airflow article building cases data dataengineering data engineers dbt definitions elt engineers etl explore extract extraction introduction pipelines pivotal processes processing recommendations role snowflake transformation use cases

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Robotics Technician - 3rd Shift

@ GXO Logistics | Perris, CA, US, 92571