ETL technology is used to extract data from source databases, transform
and cleanse the data and load it into a target database. ETL is an
important component in the set Data Warehousing technologies.
The principal differences between ETL and conventional methods of moving
data is its ease-of-use. A user friendly graphical interfaces is
available to quickly map tables and columns between the source and target
databases. This is much faster than having to write and maintain
conventional computer programs.
ETL also provides functionality to transform data values. For
example, a source system might store months of the year as "01", "02"...
"12" whereas another system might use a different convention (e.g. "Jan",
"Feb"... "Dec"). ETL facilitates transformation of data values which
is very important when data is being consolidated from multiple systems.
ETL technology can migrate data from different types of data structures
(e.g. databases, flat files) and across different platforms (e.g. mainframe,
server). It is also able to identify "delta" changes as they occur.
This allows ETL tools to copy only changed data, rather than having to do
full data refreshes that can take much time and degrade system performance.
Consequently, ETL can copied operational databases into Data Warehouses
environments in real-time or near real-time.
