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Data Warehousing Introduction
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Text and Resources The Data Warehouse Lifecycle Toolkit, Kimball, Reeves, Ross, and Thornthwaite Internet resources Data Warehousing Institute Teradata Institute Intelligent Enterprise
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Data Warehouse Approach An old idea with a new interest: Cheap Computing Power Special Purpose Hardware New Data Structures Intelligent Software Heightened Business Competition
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Data Warehouse “Queryable source of data in the enterprise” Common source of consistent organizational information Identify problems and opportunities User focused Retrieval focused
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Goals of the Course Understand the Data Warehouse philosophy Dimensional modeling Tools for Warehouse management Business intelligence Business practice
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What To Expect Help develop course expectations for the future Two tests Exercises and a semester project Graduate Presentation
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What is a data warehouse? A database filled with large volumes of cross-indexed historical business information that users can access with various query tools. The warehouse usually resides on its own server and is separate from the transaction- processing or “run- the-business” systems.
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Purpose of a data warehouse Provides an architecture for the flow of data from operational systems to decision support systems DW involves a many record analysis, during which all data has to be locked Used to discover trends and patterns Present opportunities Identify problems
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ROI of data warehouses New insights into Customer habits Developing new products Selling more products Cost savings and revenue increases Cross-selling of products Less mainframe computer storage Identify and target most profitable customers Capital outlay and development/training time can be extraordinary. Quality of system output Levels of risk Intangibles Cio.com (middle ground)
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Course Outline Introduction and basic principles Data extraction: SQL data definition code Warehouse Architecture: Dimensional Modeling Data Cleansing: SAS Datastep coding Data Presentation: MS Analysis Services
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