What Is Data Warehousing? Its Uses and Applications for Managers

6829 Words Nov 7th, 2011 28 Pages
Many corporations are experiencing significant business benefits of using data warehouse technology. Users report gains in market competitiveness through increased revenue and reduced costs through information management. Data warehousing is thus a major issue within most organizations, and thus the development of a data warehouse with a strong base is essential. This paper aims to present the important concepts of Data Warehousing such as Data Warehousing tools and the benefits of Data Warehousing, that a manager must understand in order to execute a successful Data Warehousing project in his/her company.

Keywords: Data Warehouse Technology, Market Competitiveness, Data Warehousing tools, benefits of Data Warehousing, Data
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Sometimes non-transaction data are stored in a data warehouse - though probably 95-99% of the data usually are transaction data. Additionally, "querying and reporting" rather than "query and analysis" is a key when talking about the functionality of data warehousing because the main output from data warehouse systems are either tabular listings (queries) with minimal formatting or highly formatted "formal" reports. Queries and reports generated from data stored in a data warehouse may or may not be used for analysis. (Greenfield) Nevertheless, data warehousing doesn't just make data available. Data warehousing is the process of making your operational data available to your business managers and decision support applications. Proper warehousing focuses on efficient information access. Of course, this efficiency doesn't happen magically. Corporations must first identify what it is that they require from the data and the decision support applications, and then they must evaluate the current operational data to determine how to transform that data into what adds value to the output provided by the corporations. The tools that you choose for your warehousing solution will take data from your operational systems (extract it), convert your operational data into business information using your defined business rules (transform it), and create a data warehouse (load it). (www.sas.com/rnd/warehousing) Finally,

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