The word data warehouse was first developed by Bill Inmon in the early 1990s. He referred to it as being a integrated collection of information that could help companies and organizations make better decisions.To be effective, a data warehouse had to be integrated, subject oriented, non-volatile, and time variant. In this article, I will go over all these factors in detail. If you are building a datawarehouse, it is important for you to understand why they are important.
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.
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