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Data Warehousing

  • Date Submitted: 06/25/2011 07:57 AM
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Data Warehousing - An Overview
The data warehouses are supposed to provide storage, functionality and responsiveness to queries beyond the capabilities of today's transaction-oriented databases. Also data warehouses are set to improve the data access performance of databases. Traditional databases balance the requirement of data access with the need to ensure integrity of data. In present day organizations, users of data are often completely removed from the data sources. Many people only need read-access to data, but still need a very rapid access to a larger volume of data than can conveniently by downloaded to the desktop. Often such data comes from multiple databases. Because many of the analyses performed are recurrent and predictable, software vendors and systems support staff have begun to design systems to support these functions. Currently there comes a necessity for providing decision makers from middle management upward with information at the correct level of detail to support decision-making. Data warehousing, online analytical processing (OLAP) and data mining provide this functionality.
Here, we are to discuss what is all about data warehouse, how it helps to gain a competitive edge for an organization.
Data Warehouse - An Introduction
A data warehouse is defined as a subject-oriented, integrated, nonvolatile, time-variant collection of data in support of management's decisions. More generally, data warehousing is a collection of decision support technologies, aimed at enabling the knowledge worker, such as executive, manager, and analyst, to arrive at better and faster decisions. Data warehouses provide access to data for complex analysis, knowledge discovery, and decision-making. style="mso-spacerun: They support high performance demands on an organization's data and information. It provides an enormous amount of historical and static data from three tiers:
  1. Relational databases
  2. Multidimensional OLAP applications


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