ELT is a process of gathering information from any number of sources, loading it into a location for processing, and then transforming it into actionable decision data.
Extraction - The first step, works the same way in both approaches to data management. Raw data streams from a virtual infrastructure, software and applications are ingested entirely or according to predefined rules.
Loading - This is where the ELT branch separates itself from its ETL cousin. Rather than providing so much raw data and loading it onto a temporary processing server before transformation, ELT delivers all the data to the site where it will then reside. This reduces the cycle between retrieval and delivery, but requires much more work before the data becomes useful.
Transformation - The database or warehouse sorts and normalizes the data, retaining only some or all of it so that it is accessible for custom reporting purposes. The storage load for such a large amount of data is greater, but it provides more opportunities for personalized exploration for relevant business intelligence data in near real time.