In today’s data-driven world, businesses rely heavily on data pipelines to move and transform data from various sources into a centralized location for analysis and decision-making. Two of the most common approaches in data engineering are ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform). Both are crucial, but choosing the right one can significantly impact the efficiency and effectiveness of your data processing. In this blog post, we'll explore ETL and ELT, their differences and advantages, and when to choose each for your data pipeline.

Utilize the visual interface provided by IICS to design workflows that define how user data will be integrated and transformed.