Q: How is an information warehouse project different than a typical project for a transaction system. Additionally, how would the required skill set for an information warehouse architect differ from an enterprise data architect?
A typical project for a transaction system has well defined requirements, a specific set of users, requires traditional skills and is usually delivered on known and proven technology platforms. Therefore, it can be organized and managed with a traditional waterfall methodology (although in my opinion all projects should convert to agile methodologies). On data warehouse projects, the requirements are usually a "moving target," the scope is usually too large for the deadline, data integration and data quality prove more difficult than expected, the staff often lacks business intelligence (BI) skills, communication between staff members takes too long, the tools do not live up to their expectations, and the roles and responsibilities assigned in a traditional way seem to result in too much rework. Therefore, a traditional methodology and a traditional project management approach does not work for controlling data warehouse (DW) project activities. An agile and spiral methodology is needed that is based on "extreme scoping," i.e., delivering an application in a series of short releases while "refactoring" the application deliverables (similar to the XP approach). This type of methodology requires a different project organization, such as a small self-organizing core team, shifted and shared roles and responsibilities, direct end-user involvement, etc. (Reference: Business Intelligence Roadmap by Larissa Moss and Shaku Atre, Addison Wesley, 2003).
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