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Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide

You're reading from   Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide Get to grips with Microsoft Business Intelligence and Data Warehousing technologies using this practical guide

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Product type Paperback
Published in May 2014
Publisher
ISBN-13 9781849688888
Length 350 pages
Edition Edition
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Authors (2):
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Reza Rad Reza Rad
Author Profile Icon Reza Rad
Reza Rad
Abolfazl Radgoudarzi Abolfazl Radgoudarzi
Author Profile Icon Abolfazl Radgoudarzi
Abolfazl Radgoudarzi
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Table of Contents (19) Chapters Close

Microsoft SQL Server 2014 Business Intelligence Development Beginner's Guide
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Data Warehouse Design 2. SQL Server Analysis Services Multidimensional Cube Development FREE CHAPTER 3. Tabular Model Development of SQL Server Analysis Services 4. ETL with Integration Services 5. Master Data Management 6. Data Quality and Data Cleansing 7. Data Mining – Descriptive Models in SSAS 8. Identifying Data Patterns – Predictive Models in SSAS 9. Reporting Services 10. Dashboard Design 11. Power BI 12. Integrating Reports in Applications Index

Time for action – running DMX queries from a .NET application


In this example, we will deploy the existing predictive data mining model to Analysis Services. Then, we will use a DMX query in the .NET application to create a PREDICTION JOIN between the mining model and the raw data in a database table. As a result, we will have a model applied to the dataset through C#, .NET, and DMX. Perform the following steps to run queries from an application:

  1. Open the source code of Chapter 8, Identifying Data Patterns – Predictive Models in SSAS, which is Chapter 08 Data Mining Predictive Models.sln in SSDT.

  2. Right-click on the project (not the solution) and go to Properties in the pop-up menu.

  3. In the Property Page menu, go to the Deployment tab, and change Database to Chapter 08 Data Mining Predictive Models. Then, click on OK and deploy the project, as shown in the following screenshot:

  4. After successful deployment of the project, open SSMS and connect to your local SSAS Multidimensional engine. In that...

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