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logical repository of atomic data, drawn and integrated from operational data sources. This information is dimensional in structure and may be queried directly. Optional second-line data marts, composed of derived and aggregate tables, may supplement this information. Both are populated by ETL processes. W.H. Inmon s Corporate Information Factory architecture also calls for the establishment of an integrated repository of atomic data. This repository is called the enterprise data warehouse. Unlike Kimball s repository, it is not dimensional, nor is it queried directly. Instead, this repository serves as the data source for star schema data marts. All layers are populated by ETL processes. (Note that Inmon reserves this term for the first stage only; the second is referred to as data presentation.) Stand-alone data marts do not involve an integrated repository of enterprise data. They are developed without an enterprise context, focused instead on a single subject area. An ETL process draws data directly from operational sources to populate the data mart. Although these three architectures are organized differently, all require that information from source systems eventually make its way into a star schema. A developer charged with populating a star schema in a Corporate Information Factory may have an easier job: there is a single source of data, which has already been integrated and standardized. In all cases, however, the same fundamental processing requirements must be met. asp.net gs1 128 EAN - 128 ASP . NET Control - EAN - 128 barcode generator with free ...
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Barcode Rendering Framework Release.3.1.10729 components for Asp . Net , from http://barcoderender.codeplex.com/ The bar- code rendering framework quite ... Understanding how a star schema is loaded begins with recognizing a fundamental dependency: each fact table row contains foreign key references to dimension table rows. This implies that before a row can be inserted into a fact table, the appropriate dimension rows must be ready. This high-level dependency is depicted in Figure 17-1. With this high-level dependency in mind, the discussion that follows will consider dimension processing first and then look at fact table processing. Dimension processing, represented by step 1, will be decomposed into a series of activities that must be executed for each of the dimension tables in a given star. In most situations, there are no dependencies among the dimensions themselves. This means, for example, that processes for loading product, 1 2 customer, and salesperson may take place Process Process End simultaneously. After considering dimension dimension fact table data rows processing, we will break step 2 down into a series of activities that must be executed to load the fact table. Figure 17-1 Loading a star $0.00 Bear in mind that the actual load process may or may not execute these tasks separately. Load processing is usually broken up into one module or program for each warehouse table. When this is the case, execution of these modules is organized to reflect the dependencies among the tables; dimensions are loaded first, then fact tables. It is possible, however, to develop a single module that loads the tables of a star simultaneously. For example, a system that loads a schema in real time may process transactions individually, as they occur. It is possible to define a single SQL transaction that inserts a row into the fact table and simultaneously applies necessary changes to the dimensions. Such a module must still ensure the referential integrity between fact tables and dimension tables. Loading a dimension table is an incremental process, not a one-time-only affair. It is necessary to inspect the data sources of dimension tables for new and changed information on a regular basis, and insert or update records as appropriate. These basic requirements have significant implications on the ETL process. asp.net ean 128 Where can I find a font to generate EAN 128 bar-codes? - Stack ...
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