Extract, Load, Transform (ELT) is a data integration process for transferring raw data from a source server to a data warehouse on a target server and then preparing the information for downstream uses.
ELT is a variation of the Extract, Transform, Load (ETL), a data integration process in which transformation takes place on an intermediate server before it is loaded into the target. In contrast, ELT allows raw data to be loaded directly into the target and transformed there. This capability is most useful for processing the large data sets required for business intelligence (BI) and big data analytics.
One of the main attractions of ELT is its reduction in load times relative to the ETL model. Taking advantage of the processing capability built into a data warehousing infrastructure reduces the time that data spends in transit and is more cost-effective.
Should you invest in a graph DBMS?