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Practical DMX Queries for Microsoft SQL Server Analysis Services 2008

ISBN10: 0071748660 | ISBN13: 9780071748667

Practical DMX Queries for Microsoft SQL Server Analysis Services 2008
ISBN10: 0071748660
ISBN13: 9780071748667
By Art Tennick

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Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. 250+ Ready-to-Use, Powerful DMX Queries Transform data mining model information into actionable business intelligence using the Data Mining Extensions (DMX) language. Practical DMX Queries for Microsoft SQL Server Analysis Services 2008 contains more than 250 downloadable DMX queries you can use to extract and visualize data. The application, syntax, and results of each query are described in detail. The book emphasizes DMX for use in SSMS against SSAS, but the queries also apply to SSRS, SSIS, DMX in SQL, WinForms, WebForms, and many other applications. Techniques for generating DMX syntax from graphical tools are also demonstrated in this valuable resource. View cases within data mining structures and models using DMX Case queries Examine the content of a data mining model with DMX Content queries Perform DMX Prediction queries based on the Decision Trees algorithm and the Time Series algorithm Run Prediction and Cluster queries based on the Clustering algorithm Execute Prediction queries with Association and Sequence Clustering algorithms Use DMX DDL queries to create, alter, drop, back up, and restore data mining objects Display various parameters for each algorithm with Schema queries Examine the values of discrete, discretized, and continuous structure columns using Column queries Use graphical interfaces to generate Prediction, Content, Cluster, and DDL queries Deliver DMX query results to end users Download the source code from www.mhprofessional.com/computingdownload

Chapter 1 Cases Queries
Chapter 2 Content Queries
Chapter 3 Prediction Queries with Decision Trees
Chapter 4 Prediction Queries with Time Series
Chapter 5 Prediction and Cluster Queries with Clustering
Chapter 6 Prediction Queries with Association and Sequence Clustering
Chapter 7 DDL (data definition language) Queries
Chapter 8 Schema and Column Queries
Chapter 9 After You Finish
Appendix A Graphical Content Queries
Appendix B Graphical Prediction Queries
Appendix C Graphical DDL Queries

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