Building the Data Warehouse

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When data is organized around the subject-in this case, the customer—each key has an element of time, as shown in Figure 2.9.


customer ID


customer ID


from data to date


customer ID


from date to date name address phone dob sex


name


address


credit rating


employer


dob


sex


month


number of transactions average tx amount tx high tx low


txs cancelled


customer ID


activity date


customer ID


amount


location


activity date


amount location for item invoice no clerk ID order no


order no line item no sales amount invoice no deliver to

Figure 2.9 Each table in the data warehouse has an element of time as a part of the key structure, usually the lower part.

Some tables are organized on a from-date-to-date basis. This is called a continuous organization of data. Other tables are organized on a cumulative monthly basis, and others on an individual date of record or activity basis. But all records have some form of date attached to the key, usually the lower part of the key.

Day 1-Day n Phenomenon


Data warehouses are not built all at once. Instead, they are designed and populated a step at a time, and as such are evolutionary, not revolutionary. The costs of building a data warehouse all at once, the resources required, and the disruption to the environment all dictate that the data warehouse be built in an orderly iterative, step-at-a-time fashion. The “big bang” approach to data warehouse development is simply an invitation to disaster and is never an appropriate alternative.

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