Your CIO has asked you to design a data warehouse to support the analytical needs of your Organization. At first this seems like a pretty straightforward request. But then after much due diligence, talking to different vendors and browsing Web sites and knowledge databases on the subject you find yourself more than a little confused. There are many different alternative architectures and implementation approaches that organizations have adopted. There is much disagreement on the pros and cons of one approach versus another, Industry experts often disagree with one another. Does this mean that any approach is OK? Are there any pitfalls if you choose the wrong approach, and what are the implications for your organization if you choose one approach over another? This article attempts to put some context around the confusion of picking the best architecture and approach and provides several considerations you should ponder to help you make the best choice for your organization.

 

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