Download Building and Maintaining a Data Warehouse by Fon Silvers PDF

By Fon Silvers

Because it is with development a home, lots of the paintings essential to construct a knowledge warehouse is neither obvious nor seen while taking a look at the finished product. whereas it can be effortless to plot for an information warehouse that comes with the entire correct innovations, taking the stairs had to create a warehouse that's as practical and hassle-free because it is theoretically sound, isn't really particularly effortless. That’s the problem that construction and Maintaininga information Warehouse solutions.
Based on a starting place of industry-accepted ideas, this paintings offers an easy-to-follow method that's cohesive and holistic. through delivering the point of view of a winning facts warehouse, in addition to that of a failed one, this workdetails these components that has to be entire and those who are top shunned.
Organized to logically development from extra common to express info, this important advisor: <UL> • offers components of a knowledge warehouse separately and in series, displaying how every piece turns into a operating a part of the total
• Examines the techniques and rules which are on the beginning of each profitable info warehouse
• Explains how you can realize and attend to challenging gaps in a longtime facts warehouse
• presents the massive photograph point of view that planners and managers require
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Those contemplating the making plans and construction of an information warehouse, in addition to these who’ve already equipped one will revenue drastically from the insights garnered by way of the writer in the course of his years of making and collecting details on state of the art facts warehouses which are available, handy, and reliable.

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Extra info for Building and Maintaining a Data Warehouse

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16. Louis Agosta, The Essential Guide to Data Warehousing (Upper Saddle River, NJ: Prentice Hall PTR, 2000). indb 20 2/7/08 9:52:34 AM Chapter 3 Source System Analysis Introduction A data warehouse expresses the enterprise through its data. An enterprise can be any organization capable of funding, owning and operating a data warehouse, including a corporation, educational institution, department or extremely solvent individual. A data warehouse expresses an enterprise, much like a mirror expresses a reflection, by reflecting the subject areas, entities, attributes and processes of that enterprise by the data structures in the data warehouse and the data which is integrated into those data structures.

Nonarithmetic numeric data usually occurs when the enterprise needs to uniquely identify multiple instances of an entity. Common examples include building number, part number, and employee number. The numbers used to identify such enterprise entities do not have arithmetic properties. This information will be useful in data warehouse design. If these numbers are brought into the data warehouse as numeric data, data warehouse customers will be tempted to perform arithmetic operations on them. , a 32-digit unique identifier), the data warehouse Relational Database Management System (RDBMS) will consume unnecessary space if it tries to store this data value as a 32-digit number.

But, rather than name all the species, we simply use the word dog. n Do the multiple Systems of Record indicate that a single data element is fragmented within the enterprise and must be recombined into a complete and cohesive data element in the data warehouse? If so, then Source System Analysis has identified an early requirement for the data acquisition and integration phase of data warehouse design and a risk to the quality of data in the data warehouse. Source System Analysis includes a search for those datasets, applications, etc.

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