Practical DMX Queries for Microsoft SQL Server Analysis Services 2008
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A termék adatai:
- Kiadó McGraw Hill
- Megjelenés dátuma 2010. november 16.
- ISBN 9780071748667
- Kötéstípus Puhakötés
- Terjedelem336 oldal
- Méret 228x188x17 mm
- Súly 583 g
- Nyelv angol 0
Kategóriák
Rövid leírás:
Featuring 240+ ready-to-use DMX queries, this hands-on guide explains how to extract real, actionable business intelligence?and increase effective decision-making.
TöbbHosszú leírás:
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
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
TöbbTartalomjegyzék:
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
