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  <titleInfo>
    <title>Practical DMX queries for Microsoft SQL Server Analysis Services 2008</title>
  </titleInfo>
  <titleInfo type="alternative">
    <title>Practical data mining extensions for SQL server analysis services</title>
  </titleInfo>
  <name type="personal">
    <namePart>Tennick, Art.</namePart>
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    <place>
      <placeTerm type="text">New York</placeTerm>
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    <publisher>McGraw-Hill</publisher>
    <dateIssued>2010</dateIssued>
    <dateIssued encoding="marc">2011</dateIssued>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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    <extent>xxvi, 308 p. : ill. ; 23 cm.</extent>
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  <abstract>"250+ Ready-to-Use, Powerful DMX QueriesTransform 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"--</abstract>
  <abstract>"Transform data mining model information into actionable business intelligence using the Data Mining Extensions (DMX) language. Practical DMX Queries for Microsoftʼ SQL Serverʼ 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"--</abstract>
  <tableOfContents>Machine generated contents note: 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.</tableOfContents>
  <note type="statement of responsibility">Art Tennick.</note>
  <note>Includes index.</note>
  <subject authority="lcsh">
    <titleInfo>
      <title>SQL server</title>
    </titleInfo>
  </subject>
  <subject authority="lcsh">
    <topic>Data mining</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Querying (Computer science)</topic>
  </subject>
  <subject authority="bisacsh.">
    <topic>COMPUTERS / Certification Guides / General</topic>
  </subject>
  <classification authority="lcc">QA76.9.D343 T365 2011</classification>
  <classification authority="ddc" edition="22">005.7585 TAP</classification>
  <classification authority="bisacsh">COM055000</classification>
  <identifier type="isbn">9780071748667 (pbk.)</identifier>
  <identifier type="lccn">2010037506</identifier>
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    <recordChangeDate encoding="iso8601">20150408114157.0</recordChangeDate>
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