From the course: Complete Guide to Analytics Engineering
Join today to access over 25,300 courses taught by industry experts.
ETL vs. ELT
From the course: Complete Guide to Analytics Engineering
ETL vs. ELT
- [Narrator] In the last video, we explored the basics of ETL and data pipelines. As you recall, ETL stands for extract, transform, load. In recent years, a new version of Data Pipeline has come on the scene that is especially popular with analytics engineers. It's called ELT, or extract, load, transform. The difference is when the transformation step takes place. Rather than transforming the data before we bring it in the database, we just bring the raw data or slightly altered data straight into the database, and then perform the transformations with data models, often in SQL at a later date. In contrast to ETL, ELT processes data by first extracting and loading it in its original schema and structure directly into the data warehouse. The transformation can occur within the warehouse, either immediately after or at a later date. This change in the order of operations can occur because modern data infrastructure can take advantage of cloud data warehouses, such as Snowflake, Google…
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.