COMPONENTS OF DATA WAREHOUSING

Data warehousing components are identified in the figure above. A detailed discussion
of each of the components will be followed as we move along.


Data Mart -- A data mart is a focused subset of a data warehouse that deals with a single area of data and is organised for quick analysis.

Metadata -- Literally, "data about data." It is the descriptions of what kind of information is stored where, how it is encoded, how it is related to other information, where it comes from, and how it is related to your business.

Query -- A specific atomic request for information from a database.

Data Mining -- Data mining is the running of automated routines that search through data organised in a warehouse. They look for patterns in order to point you to areas that you should be addressing.

OLAP (On-Line Analytical Processing) -- Tools that extract data from data warehouses go by a variety of names: OLAP, ROLAP (Relational On-Line Analytical Processing), multi-dimensional analysis tools, and decision support systems being the most common ones. All provide the ability to do rapid analysis of multiple simultaneous factors, something that relational databases can't do.

Data Visualization --Techniques for turning data into information by using the high capacity of the human brain to visually recognise patterns and trends. There are many specialised techniques designed to make particular kinds of visualization easy.