What Is ETL?
ETL stands for Extract, Transform, Load. It’s a data integration process where data is:
- Extracted from source systems,
- Transformed into a usable format, and
- Loaded into a data warehouse or analytics platform.
This process is essential for consolidating and preparing large volumes of data for analysis and reporting. The transformation step is particularly important, as it ensures the data is clean, consistent, and aligned with the goals of the business or project.
ETL vs ELT
When comparing ETL to ELT (Extract, Load, Transform), the primary difference lies in the sequence of operations. While ETL performs transformations before loading data into the target system, ELT loads raw data into the target first and performs the transformations within the system itself. ELT is often favored in modern data architectures that leverage powerful cloud-based data warehouses, as it allows for faster data ingestion and utilizes the computational power of the target system for transformations. On the other hand, ETL is typically suited for scenarios where data transformations need to happen outside the target system or when working with legacy systems with limited processing capacity.