A
data warehouse is a repository of transactional data that has been extracted
from original electronic sources and transformed so that query, analysis and
reporting on trends within historic data are possible and efficient. The
analyses provided by data warehouses may involve strategic planning, decision
support, and monitoring the outcomes of a chosen strategy. Typically, data that
is loaded into a data warehouse is derived from diverse sources of operational
data, which may consist of data from databases, feeds, xml files, application
files or flat files. The data must be extracted from these diverse sources,
transformed to a common format, and loaded into the data warehouse. Typically,
it is further aggregated into a data mart for efficient reporting. The ETL (Extract,
transform and load) process is a critical step in any data warehouse
implementation, and continues to be an area of major significance whenever the
ETL code is updated. Once the data warehouse and data marts are populated,
business intelligence applications facilitate querying, analysis and reporting.
The business intelligence tools may provide simple presentations of data based
on queries, or may support sophisticated statistical analysis options. Data
warehouses may have multiple front-end applications, depending on the needs of
the user community.