Building the Data Warehouse

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Operational Development/DSS Development


The data-driven methodology will be presented in three parts: METH 1, METH 2, and METH 3. The first part of the methodology, METH 1, is for operational systems and processing. This part of the methodology will probably be most familiar to those used to looking at classically structured operational methodologies. METH 2 is for DSS systems and processing—the data warehouse. The essence of this component of the methodology is a data model as the vehicle that allows the commonality of data to be recognized. It is in this section of the appendix that the development of the data warehouse is described. The third part of the methodology, METH 3, describes what occurs in the heuristic component of the development process. It is in METH 3 that the usage of the warehouse is described.

Summary


In this chapter, a migration plan and a methodology (found in the appendix) were described. The migration plan addresses the issues of transforming data out of the existing systems environment into the data warehouse environment. In addition, the dynamics of how the operational environment might be organized were discussed.


The data warehouse is built iteratively. It is a mistake to build and populate major portions of the data warehouse—especially at the beginning—because the end user operates in what can be termed the “mode of discovery.” The end user cannot articulate what he or she wants until the possibilities are known.


The process of integration and transformation of data typically consumes up to 80 percent of development resources. In recent years, ETL software has automated the legacy-to-data-warehouse interface development process.

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