Practical DMX Queries for Microsoft SQL Server Analysis Services 2008

  • 2h 49m
  • Art Tennick
  • McGraw-Hill/Osborne
  • 2011

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

About the Author

Art Tennick has worked in relational database design and SQL queries for more than 20 years. He has been involved in multi-dimensional database design, cubes, data mining, DMX, and MDX for 10 years. Art is the author of Practical MDX Queries for Microsoft SQL Server Analysis Services 2008 and Practical PowerPivot & DAX Formulas for Excel 2010.

In this Book

  • Cases Queries
  • Content Queries
  • Prediction Queries with Decision Trees
  • Prediction Queries with Time Series
  • Prediction and Cluster Queries with Clustering
  • Prediction Queries with Association and Sequence Clustering
  • Data Definition Language (DDL) Queries
  • Schema and Column Queries
  • After You Finish