Data is extracted from one or more sources, transformed into a homogenous format ready for analysis and then loaded into a target. The transformation "T" may be done on an intermediate server, i.e., between the sources and the target, or else processed within the target destination.

The transformation process is highly compute intensive and often represents the major bottleneck for data teams awaiting data sets for analysis and application of ML algorithms.

Bodo transforms data in a fraction of the time in comparison to traditional approaches and can therefore cut 90% of both time and hardware costs in terms of data processing.