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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
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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

An introduction to data mining


Data mining is the process of finding the problem, thinking about the solution, testing data mining models on a test dataset, and deploying one or more mining models in a live environment. The data mining process does not conclude at any of these steps; it is a circular process that continues to improve data analysis with time.

The following diagram shows the data mining process with Microsoft tools (sourced from Microsoft, http://technet.microsoft.com/en-us/library/ms174949.aspx):

The set of data on which mining algorithms will be applied are called training and test case. There are many data mining algorithms designed and introduced in academic research. Microsoft implemented nine of the most common data mining algorithms as part of the SQL Server product. The following is a list of data mining algorithms and a few lines of information about their usage in solving real-world problems:

  • Decision tree: This algorithm creates a tree based on the attribute values...

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