ETL (extract, transform, load)
A data integration pattern that extracts data from source systems, transforms it into the required structure and loads it into a destination such as a warehouse. In the related ELT pattern, raw data is loaded first and transformed inside the destination platform.
Why it matters
ETL and ELT are how most organisations populate their analytical platforms. The choice between them affects cost, flexibility and governance: ELT keeps raw data available for reprocessing, while ETL can prevent sensitive or unnecessary data from reaching the platform at all.
Whichever pattern is used, transformation logic encodes business definitions and should be version-controlled, tested and reviewed like application code.
In practice
For example, a UK property group might use ELT to load raw lease and rent-roll data into its warehouse, then transform it into tenancy, arrears and occupancy tables, while using ETL to strip bank details before they leave the finance system.
Where Rodan fits
Rodan designs integration patterns suited to each source and use in Data and Analytics Engineering work.