Building the Data Warehouse

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•    what needs to be fixed


•    the estimate of resources required


•    the order of work


•    the disruption analysis


Figure 9.7 The first steps in creating the operational cleanup plan.


describes how to use the data warehouse. In addition, the classical activities of operational development are included to form what can be termed a data-driven methodology.


The methodology described differs from the migration path in several ways. The migration path describes general activities dynamically. The methodology describes specific activities, deliverables from those activities, and the order of the activities. The iterative dynamics of creating a warehouse are not described, though. In other words, the migration plan describes a sketchy plan in three dimensions, while the methodology describes a detailed plan in one dimension. Together they form a complete picture of what is required to build the data warehouse.

A Data-Driven Development Methodology


Development methodologies are quite appealing to the intellect. After all, methodology directs the developer down a rational path, pointing out what needs to be done, in what order, and how long the activity should take. However, as attractive as the notion of a methodology is, the industry track record has not been good. Across the board, the enthusiasm for methodologies (data warehouse or any other) has met with disappointment on implementation.


Why have methodologies been disappointing? The reasons are many:


■■ Methodologies generally show a flat, linear flow of activities. In fact,


almost any methodology requires execution in terms of iterations. In other words, it is absolutely normal to execute two or three steps, stop, and repeat all or part of those steps again. Methodologies usually don’t recognize the need to revisit one or more activities. In the case of the data warehouse, this lack of support for iterations makes a methodology a very questionable subject.

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