By Claude Seidman
Your organizational database is barely pretty much as good because the strategic information you could extract from it. Do consumers who purchase breakfast cereal regularly purchase bananas in addition? Is there a correlation among rainfall in a specific sector and the superiority of a selected affliction there? facts Mining with Microsoft SQL Server 2000 Technical Reference indicates tips on how to use Microsoft's research instruments for giant databases. writer Claude Seidman bargains recommendation at the data-modeling engineering method as a complete, together with designing innovations more likely to yield significant effects, designing info warehouses, becoming choice bushes, recognizing clusters and anomalies in facts, and automating mining methods with code.Despite its designation as a reference, this publication is basically an academic - you will confer with it for suggestion on tips to make research prone do whatever specifically. Seidman makes use of a vintage and powerful instructional method, sticking with an instance in the course of the publication and including to past examples as he explores extra features of Microsoft information mining. His representation consists of deciding on safe to eat mushrooms, according to a database of proof approximately identified mushrooms, and he is mixed how-to prose with display photographs and amassed knowledge to nice impression. in the event that your association has long past with Microsoft SQL Server 2000 for info garage, learn this e-book for recommendation on wisdom extraction.
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Extra resources for Data Mining with Microsoft® SQL Server™ 2000 Technical Reference
The database administrator typically specifies one or more levels for each OLAP dimension. Hierarchies, which specify the parent-child relationships between the levels. The database administrator typically specifies at least one hierarchy for each OLAP dimension. If there is only one level for the dimension, then no hierarchy is specified and the dimension is a simple, non-hierarchical list. Attributes, which record characteristics of the level elements for the dimension. For example, an attribute might record the gender of each customer in the customers dimension.
2-18 Oracle9i OLAP Services Developer’s Guide to the Oracle OLAP API MdmMeasure Class The following table lists the elements of an MdmListDimension called mdmColor. Elements of mdmColor Black Blue Cyan Green Magenta Red Yellow White MdmMeasure Class Description of an MdmMeasure An MdmMeasure represents a set of data that is organized by one or more MdmDimension objects. The structure of the data is similar to that of a multidimensional array. Like the dimensions of an array, the MdmDimension objects that organize an MdmMeasure provide the indexes for identifying individual cells.
A level MdmHierarchy has an MdmUnionDimensionDefinition, and its regions are MdmLevel objects. The return value from its getHierarchyType method is LEVEL_HIERARCHY. A level MdmHierarchy is based on a hierarchy that was defined by a database administrator in the OLAP management feature of Oracle Enterprise Manager. ■ Union MdmHierarchy, which represents a dimension that has one or more subordinate hierarchical structures. These structures are represented by one or more level MdmHierarchy objects.