From the course: Complete Guide to Data Lakes and Lakehouses

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ETL vs. ELT

ETL vs. ELT

From the course: Complete Guide to Data Lakes and Lakehouses

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ETL vs. ELT

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- We talked about data ingestion in the previous video, and now I think it is important to clarify what are the steps involved for such data movement to happen. Sure, there is some type of extraction from the source and loading data in the data lake happening, but is there any more processing involved? Does it happen before or after loading the data? Let's clarify those points. ETL, which stands for extract, transform, and load, involves extracting data from source systems, transforming it into a structured format, and then loading it into a target database, data warehouse or data lake. In ETL, the heavy lifting of data transformation occurs before data enters the data warehouse or data lake. This approach is preferred when data integrity and cleanliness are priorities. ETL is ideal for scenarios where data needs to be aggregated and transformed from various sources in a uniform way before storing it, or when we need to handle sensitive information so it doesn't make it to the target…

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