Data Mining Enhancements
Data mining technology analyzes data in relational databases and OLAP cubes to discover information of interest. The data mining features of Microsoft® SQL Server™ 2000 Analysis Services are incorporated in an open and extensible implementation of the new OLE DB for Data Mining specification. SQL Server 2000 includes data mining algorithms developed by Microsoft Research.
Relational and OLAP Data Mining
Analysis Services has incorporated data mining technology so that you can use it to discover information in relational databases and in OLAP cubes in Analysis Services. You can use the results of data mining to create a dimension that you can add to a cube to further analyze your data. For more information, see Data Mining Models.
Microsoft Decision Trees
The Microsoft Decision Trees algorithm uses classification techniques to analyze data. It then constructs one or more decision trees that can be used to predict attributes or values for new data. For example, you can use this algorithm to analyze credit history data and predict the credit risk of new applicants. For more information, see Microsoft Decision Trees.
Microsoft Clustering
The Microsoft Clustering algorithm uses a nearest neighbor method to group records into clusters that share similar characteristics. Often, these characteristics may be hidden or nonintuitive. For more information, see Microsoft Clustering.
Data Mining User Interface
Analysis Services provides new user interface wizards, dialog boxes, and editors to help you quickly perform data mining administrative tasks such as building data mining models and incorporating the results in OLAP cubes. You can browse a single decision tree model or the dependency network model of multiple trees produced when multiple attributes are predicted. For more information, see Building and Using Data Mining Models.
MDX Extensions for Data Mining
Multidimensional Expressions (MDX) syntax has been extended to provide data mining capabilities in connection with OLAP cubes. For more information, see MDX.
DTS Tasks for Data Mining
The Analysis Services Processing task has been enhanced to allow processing mining models, and a new Data Transformation Services (DTS) task is provided that you can use to create predictions from mining models. For more information, see Automating and Scheduling Administrative Tasks.
Data Mining in Client Applications
Client applications for Analysis Services can use data mining algorithms to discover information in OLAP cubes by creating data mining models and virtual cubes. For more information, see Advanced Data Mining and Analysis.