• Under estimating the complexity of the project.  As the span of the project increase to cover multiple functional areas and business units, the complexity grows geometrically.
• Failure to understand the key element - the data.  Far to many implementations focus on a specific tool as the key.  Rather it's the data that's the key.  Obtaining the data, validating the data, rationalizing the data, setting up the loads, etc.  This is where most of work is needed and most of the problems occur.
• Viewing it from an System Development Life Cycle (SDLC) perspective.  This is the proper way to view the development of an accounting system or an order-ship-bill system.  And while the discipline is needed it can cause problems.  One of the key assumptions is that you have a straight line process - obtains specifications, then develop units, test units, system test and roll out.  Unfortunately, the process needed is far more iterative in nature.  People can only give an approximation of the what they need.  So small short steps are needed rather than a large project.
• Organizations try to go from nothing to a complex system in a single project.  This is a recipe for failure.  Organizations that have active Decision Support Systems and other analytical systems in place are far more likely to be successful than those that none of these. 

If your organization is considering a Data Warehouse project we have the experience to develop and implement a successful project.

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