Integrated Data

In the data warehouse, data is not stored by operational applications, but by business subjects. 

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Figure 2-1 the data warehouse is subject oriented.

In a data warehouse; there is no application flavor. The data in a data warehouse cut across applications.

Integrated Data

For proper decision making, you need 10 pull together all the relevant data from the various applications. The data in the data warehouse comes from several operational systems. Source data are in different databases, files, and data segments. These are disparate applications, so the operational platforms and operating systems could be different. The file layouts. Character code representations and field naming conventions all could be different.

In addition to data from internal operational systems. For many enterprises. Data from outside source is likely to be very important. Companies such as Metro. Mail. A. C. Nielsen, and IR I specialize in providing vital data on a regular basis. Your data warehouse may need data from such sources. This is one more variation in the mix of source data for a data warehouse.

Figure 2-2 illustrates a simple process of data integration for a banking institution. Here the data fed into the subject area of arrow:, in the data warehouse comes from three different operational applications. Even within just three applications, there could be several variations, Naming conventions could be different; attributes or data items could be different. The account number in the Savings Account application could be eight bytes long, but only six bytes in the Checking Account application.

Before die data from various disparate sources can be usefully stored in a data ware-house. you have to remove the inconsistencies. You have to standardize the various data elements and make sure ()I the meanings of data names in "each source application. Before moving the data into the data warehouse, you have to go through a process or transformation. Consolidation. And integration of the source data.