Case Study 2 (Chapter 6)

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1. What is a data warehouse and why is REI building one?
A data warehouse is unique kind of a database where current and historical data about a certain group of people such as customers, is stored. Information from operational systems, such as transaction processing systems, is extracted and summarised then stored in in a data warehouse. This type of information includes records about customer interaction patens, customer purchasing history or trends and current customer records. The information in a data warehouse is used for management analysis and decision making.

REI needs data warehouse for the following benefits
• It will help REI’s management in decision making. Drawing trends about past and current customer buying patens
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Operational business applications, such as customer relationship management (CRM) systems. Compressed data on disk to decrease disk space and storage infrastructure requirements becomes a cost effective strategy in terms of storage overheads. Easily measured and monitored financial and operational business performance, will mean predictable outcomes and planning becomes efficient.
Reduced risks and costs will make it easier for REI business expansion without fear of risks involved to a certain degree. All above strategic Practices cannot be dealt with without a data warehouse.
4. What are some of the ricks or concerns surrounding the creation of a data warehouse?
• Risks of warehousing involve: Lack of strong sponsor or sponsor not at high enough level to get people motivated.
• Lack of proper skills and experience. Most people have to go through at least one failure before they understand how different a data warehouse is from a transaction processing system or small data mart. You can have wonderful logical models, but turning those into an efficient, integrated, enterprise-wide physical design is a most difficult task.
• Not understanding what the organization needs from a data warehouse and how the data warehouse helps achieve the strategic objectives of the organization.
• Lack of a data quality project as an integral part of

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