Building the Data Warehouse

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Summary


This chapter has discussed the origins of the data warehouse and the larger architecture into which the data warehouse fits. The architecture has evolved throughout the history of the different stages of information processing. There are four levels of data and processing in the architecture—the operational level, the data warehouse level, the departmental/data mart level, and the individual level.


The data warehouse is built from the application data found in the operational environment. The application data is integrated as it passes into the data warehouse. The act of integrating data is always a complex and tedious task. Data flows from the data warehouse into the departmental/data mart environment. Data in the departmental/data mart environment is shaped by the unique processing requirements of the department.


The data warehouse is developed under a completely different development approach than that used for classical application systems. Classically applications have been developed by a life cycle known as the SDLC. The data warehouse is developed under an approach called the spiral development methodology. The spiral development approach mandates that small parts of the data warehouse be developed to completion, then other small parts of the warehouse be developed in an iterative approach.


The users of the data warehouse environment have a completely different approach to using the system. Unlike operational users who have a straightforward approach to defining their requirements, the data warehouse user operates in a mindset of discovery. The end user of the data warehouse says, “Give me what I say I want, then I can tell you what I really want.”

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