Building the Data Warehouse

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Data warehouse data must be selected, accessed, and then reshaped to meet the needs of the data mart. Often the data mart data resides in cubes. The cubes need to be formed, and many different calculations need to be performed on the detailed data that resides in the data warehouse. In short, a nontrivial process occurs as data is passed from a normalized world into a multidimensional world.


One of the important issues here is how much data must be accessed and how often is the refreshment process to be performed.

Supporting the ODS


In general there are three classes of ODS—class I, class II, and class III. In a class I ODS, updates of data from the operational environment to the ODS are synchronous. In a class II ODS, the updates between the operational environment and the ODS occur within a two-to-three-hour time frame. And in a type III ODS, the synchronization of updates between the operational environment and the ODS occurs overnight. But there is another type of ODS structure—a


class IV ODS, in which updates into the ODS from the data warehouse are unscheduled. Figure 3.57 shows this support.


The data in the data warehouse is analyzed, and periodically the data is placed in the ODS. The data that is shipped to the ODS is shipped in the form of profile data, which is data that represents many different physical occurrences of data. As a simple example of profile data, suppose the details of a customer’s transactions are analyzed. The customer has been active for several years. The analysis of the transactions in the data warehouse is used to produce the following profile information about a single customer:

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