The principal notion behind
data warehousing is that the data stored for business analysis can most
efficiently be accessed by dividing it from the data in the operational
systems. A data warehouse, therefore, is a collection of data gathered from one
or more data repositories to create a new, central database. For example an
industry may create a data warehouse by extracting the operational data it has
accumulated concerning the workers information, products they are working on,
material they are using for making the particular product, output production
and etc,. Data Warehousing is not just the data in the warehouse, but also the
architecture and tools to collect, query, analyze and present information.
The characteristics of a data
warehouse were first defined by W.H. Inmon who stated, “A data warehouse is
subject-oriented, integrated, time-variant and non-volatile [data] collection
in support of management decision making processes”. Let’s
discuss that definition down:
·
· Subject-oriented: all relevant data concerning
a subject
·
· Integrated: all data in the warehouse
must be compatible with each other regardless of type or location.
·
· Time-variant: all data contains a reference
to time so that the age of each piece of data can be determined.
·
· Non-volatile: the data does not change once
it has been collected.
