Concepts for Data Engineers: ETL x ELT x EL
In this series I’m introducing several important concepts that new Data Engineers should be aware of. The other topics I talked so far:
✅ Data Modelling
✅ CDC
✅ Idempotency
I also have 2 series about python:
🐍 Efficient Python
🐍 Software Engineering with Python
Let’s get starteeeed…
Data engineering processes are crucial for effective data integration and management. ETL (Extract, Transform, Load), ELT (Extract, Load, Transform), and EL (Extract and Load) are three approaches commonly used in data engineering workflows. ETL involves extracting data from various sources, transforming it, and loading it into a target system. ELT focuses on loading raw data into a target system first and then performing transformations within the system. EL, on the other hand, emphasizes direct loading without extensive transformations. Each approach has its own advantages and importance based on the specific requirements and characteristics of the data integration process. This article explores the significance of ETL, ELT, and EL, and provides insights into their creation and use cases in data engineering.
