1.Overview
A data warehouse is a central repository for all or significant parts of the data that an enterprise's various business systems collect. [1] The data warehousing market consists of tools, technologies, and methodologies that allow for the construction, usage, management, and maintenance of the hardware and software used for a data warehouse, as well as the actual data itself. Two of the pioneers in the field were Ralph Kimball and Bill Inmon. [2] A data warehouse has several processes that require several technology components. Batch and transaction processing data first has to be extracted from operational databases and then cleaned up to remove redundant data, fill in blank and missing fields and organized into consistent formats. The data is then loaded into a relational database. Business analysts can then dig into the data using data access and reporting software including On-Line Analytical Processing (OLAP) tools, statistical modeling tools, geographic information systems (GIS) and data mining tools.
Data warehouses are the basis for customer relationship management systems because they can be used for consolidating customer data and identifying areas of customer satisfaction and frustration. Warehouses are also used for fraud detection, product repositioning analysis, profit center discovery and corporate asset management.
Setting up a data warehouse is a tedious job. Just identifying where all a business’s data comes from, how it gets entered into a system and where it is all stored can be difficult, and setting up a data cleansing processes is quite complicated. Large data warehousing projects take years and millions of dollars to implement. [3]
2.Definitions of Terms Commonly Used
The repository provides information about the location and nature of operational data, which is critical in the construction of a data warehouse. It acts as a guide to the warehouse data, storing information necessary to define the migration environment..................
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