Data Mining with Microsoft SQL Server 2008 (Kindle Edition)
Product Description
From the Back Cover
The most authoritative book on data mining with SQL Server 2008
SQL Server Data Mining has become the most widely deployed data mining server in the industry. Business users—and even academic and scientific users—have adopted SQL Server data mining because of its scalability, availability, extensive functionality, and ease of use.
The 2008 release of SQL Server brings exciting new advances in data mining. This authoritative and up-to-date resource shows how to master all of the latest features, with practical guidance on how to deploy and use SQL Server data mining for yourself.
The author team begins with an introduction to the tools, techniques, and concepts necessary to leverage SQL Server 2008 data mining. The discussion progresses to a thorough look at the details of the SQL Server 2008 data mining algorithms. You’ll discover how to integrate SQL Server data mining into other parts of the SQL Server Business Intelligence (BI) suite and extend SQL Server data mining for your own needs. Detailed, practical examples clearly explain how to implement successful data mining solutions with SQL Server 2008.
Data Mining with Microsoft SQL Server 2008 shows you how to:
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Apply data mining solutions using Microsoft Excel
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Use the data mining Add-ins for Microsoft Office
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Understand how, when, and where to apply the algorithms that are included with SQL Server data mining
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Perform data mining on online analytical processing (OLAP) cubes
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Extend SQL Server data mining by implementing your own data mining algorithms and stored procedures
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Use SQL Server Management Studio to access and secure data mining objects
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Use SQL Server Business Intelligence Development Studio to create and manage data mining projects
The companion website includes the complete sample code and data sets that are featured in the book.
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Jamie MacLennan, ZhaoHui Tang, and Bogdan Crivat have done a superb job on this book and for those of us that had to deal with the 2005 version rest assured dear reader that the 2008 version is a ‘work of art’. The writing is clear and concise. The examples are easy to work with, understandable and gone are the complex mathmathics that required genious to interpret. I have bought a copy for myself and two for the office. I have a problem with recommending books for the sake of recommending them. Trust me the 2008 version is worth every cent!!. Thanks Jamie et Al and well done!!!!
“Data Mining with Microsoft SQL 2008″ is a great resource for learning how to perform data mining using SQL Server 2008 and Analysis Services 2008, with the added benefit that it is written by some of the people that influenced the design of the product. The presentation is clear and easy to read, and the content is rich in examples of using the Analysis Services data mining algorithms. Aspects such as how to create mining models, how to view them, and how to interpret results are covered in detail. An entire chapter is dedicated to creating plug-in algorithms, which is a powerful way of extending existing algorithms and implementing new solutions for a custom data mining problem. Another chapter covers mining data in Excel using the Data Mining Add-in for Excel, which I find to be very useful for experimenting with data sets and for quickly analyzing data. I recommend this book as a great source for gaining valuable knowledge if you are interested in Data Mining using SQL Server 2008 and Analysis Services 2008.
Disclaimer: I worked on the development of Analysis Services 2008 and I have reviewed some of the book samples.
This book was a very useful resource while developing a plug-in algorithm to the SQL Server Data Mining framework. I have had mixed results in the past trying to integrate into the framework, but both this book and the previous SQL Server 2005 version answered all my questions and helped me and my company to create a much improved product offering. With a little bit of time vague requests like “build a recommendation engine” can be turned into crowd pleasers, without having to delve into custom algorithm development and extensive research.
The price tag is a little steep, but the content is well worth it.