By P., (Author) Ponniah
Precis, and evaluate workouts on the end of every bankruptcy, Ponniah's paintings will entice IT pros who already layout, enforce, or continue information warehousing structures in addition to beginners to the topic. the fundamental parts of knowledge warehousing are defined prior to Ponniah turns to themes of undertaking administration, defining company standards, the structure and infrastructure, the function of metadata, implementation, progress, and upkeep. Ponniah first constructed this direction at a group university in North department, New Jersey.
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Extra info for Data Warehousing Fundamentals
The account number in the Savings Account application could be eight bytes long, but only six bytes in the Checking Account application. Before the data from various disparate sources can be usefully stored in a data warehouse, you have to remove the inconsistencies. You have to standardize the various data elements and make sure of the meanings of data names in each source application. Before moving the data into the data warehouse, you have to go through a process of transformation, consolidation, and integration of the source data.
For a manufacturing company, sales, shipments, and inventory are critical business subjects. For a retail store, sales at the check-out counter is a critical subject. Figure 2-1 distinguishes between how data is stored in operational systems and in the data warehouse. In the operational systems shown, data for each application is organized separately by application: order processing, consumer loans, customer billing, accounts receivable, claims processing, and savings accounts. For example, Claims is a critical business subject for an insurance company.
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 sources is likely to be very important. Companies such as Metro Mail, A. C. Nielsen, and IRI 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.
Data Warehousing Fundamentals by P., (Author) Ponniah