ETL for BI — Building Data Pipelines That Don't Break
Extract, transform, load for business intelligence: dbt, data pipelines, transformation layers, and the shift to ELT.
You have source systems generating data. You have a data warehouse waiting to receive it. The pipeline connecting them — extracting data from sources, transforming it into analytical shapes, and loading it into the warehouse — is the ETL pipeline. And if BI is only as good as the data behind it, the ETL pipeline is the most critical piece of infrastructure you'll build.
"ETL" stands for Extract, Transform, Load. But in the modern data stack, the order has flipped. Now it's ELT — Extract, Load, Transform. The difference matters, and understanding why the industry shifted will help you build pipelines that scale.
ETL vs. ELT — Why the Order Flipped
Traditional ETL
In traditional ETL, data is extracted from source systems, transformed in a staging area (often a separate server), a
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