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By C.J. Date

Provides an authoritative source for readers drawn to gaining perception into and knowing of the foundations of database structures. offers stable grounding within the foundations of database expertise and gives a few principles as to how the sector is probably going to enhance sooner or later. New seventh variation. DLC: Database administration.

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Specify any structural transformations, terminology transformations, or encoding transformations that apply within the mapping. 6. Specify any transformations that are necesFigure 3-12 Analyzing the application models. sary between model representations. For Chapter 3 SOME TYPES AND USES OF DATA MODELS Analysis AM Integration Analysis AM IM’ Integration IM’ Integration model subset Figure 3-13 Adding any missing concepts to the integration model. Subsetting Figure 3-14 Identifying the subset of the integration model.

9 Business Information Model Business information models are a type of application data model that is used in data warehouses for reporting and slicing and dicing your transaction data. Instead of being normalized in their structure, these models are arranged in terms of “facts” (transactions, typically), and the “dimensions” (such as time, geography, or product lines) used to specify reports. The simplest structure is a “star” pattern, with a fact or group of facts in the middle, and dimensions radiating out from there.

The result of this is that it is possible for a conceptual data model and a logical data model to be very similar, or even the same for the same subject area, depending on the approach that is taken with each. 4 Canonical Data Model In the context of data models, a canonical data model means a data model that is fully normalized and in which no derived data is held. So a logical data model might or might not also be a canonical data model. 5 Application Data Model An application data model is (obviously) one that relates to a particular application.

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