Building the Data Warehouse

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We are told that the hieroglyphics in Egypt are primarily the work of an accountant declaring how much grain is owed the Pharaoh. Some of the streets in Rome were laid out by civil engineers more than 2,000 years ago. Examination of bones found in archeological excavations shows that medicine—in, at least, a rudimentary form—was practiced as long as 10,000 years ago. Other professions have roots that can be traced back to antiquity. From this perspective, the profession and practice of information systems and processing is certainly immature, because it has existed only since the early 1960s.

Information processing shows this immaturity in many ways, such as its tendency to dwell on detail. There is the notion that if we get the details right, the end result will somehow take care of itself and we will achieve success. It’s like saying that if we know how to lay concrete, how to drill, and how to install nuts and bolts, we don’t have to worry about the shape or the use of the bridge we are building. Such an attitude would drive a more professionally mature civil engineer crazy. Getting all the details right does not necessarily bring more success.

The data warehouse requires an architecture that begins by looking at the whole and then works down to the particulars. Certainly, details are important throughout the data warehouse. But details are important only when viewed in a broader context.

The story of the data warehouse begins with the evolution of information and decision support systems. This broad view should help put data warehousing into clearer perspective.

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