Understand how to use the new features of Microsoft SQL Server 2008 for data mining by using the tools in Data Mining with Microsoft SQL Server 2008, which will show you how to use the SQL Server Data Mining Toolset with Office 2007 to mine and analyze data. Explore each of the major data mining algorithms, including naive bayes, decision trees, time series, clustering, association rules, and neural networks. Learn more about topics like mining OLAP databases, data mining with SQL Server Integration Services 2008, and using Microsoft data mining to solve business analysis problems.
Data Mining with Microsoft SQL Server 2008
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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:
Apply data mining solutions using Microsoft Excel
Use the data mining Add-ins for Microsoft Office
Understand how, when, and where to apply the algorithms that are included with SQL Server data mining
Perform data mining on online analytical processing (OLAP) cubes
Extend SQL Server data mining by implementing your own data mining algorithms and stored procedures
Use SQL Server Management Studio to access and secure data mining objects
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.
About the Author
Jamie MacLennan is principal development manager of the SQL Server Analysis Services at Microsoft. He has more than 25 patents or patents pending for his work on SQL Server Data Mining, and has written extensively on the data mining technology in SQL Server. ZhaoHui Tang is a principal group program manager at Microsoft adCenter and inventor of Keyword Services Platform. Bogdan Crivat is a senior software design engineer in SQL Server Analysis Services at Microsoft, working primarily on the data mining platform.
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6 of 6 people found the following review helpful:
5.0 out of 5 stars
The authoritative resource on SQL Server 2008 Data Mining,
This review is from: Data Mining with Microsoft SQL Server 2008 (Paperback)
"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.
5 of 5 people found the following review helpful:
5.0 out of 5 stars
A plug-in developer must read,
By
This review is from: Data Mining with Microsoft SQL Server 2008 (Paperback)
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.
3 of 3 people found the following review helpful:
5.0 out of 5 stars
Data Mining with Microsoft SQL Server 2008,
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This review is from: Data Mining with Microsoft SQL Server 2008 (Paperback)
This is an excellent book for beginner to expert. Contains tons of relevant information. Could have been more detailed for the beginner, but authors did as well as possible without having to write a multi-volume version. Mid level to expert users should have no problem understanding the examples and solutions used in the book. I strongly recommend this book.
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Inside This Book
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Key Phrases - Statistically Improbable Phrases (SIPs):
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prediction calculator, commute distance, education level, scenario analysis, married male, term extraction, query syntax, customer clusters, cluster profiles, prediction report, new varietal, cluster diagram, movie ratings, predictable state, address terms, web data, attribute profiles, model usage, field list, web applications, dry white, suggested threshold, attribute discrimination, data mining dimension, mining structure columns Key Phrases - Capitalized Phrases (CAPs): (learn more)
Analysis Services, Server Data Mining, Naïve Bayes, Dev Studio, Marital Status, Microsoft Decision Trees, Microsoft Association Rules, Cancel Figure, Microsoft Neural Network, Table Analysis Tools, Miles Europe, Microsoft Time Series, Microsoft Clustering, Star Wars Episode, Microsoft Sequence Clustering, Goal Seek, Home Ownership, Server Management Studio, Miles Pacific, Microsoft Logistic Regression, Reporting Services, Fill From Example, Analyze Key Influencers, Server Integration Services, State of the Union Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
prediction calculator, commute distance, education level, scenario analysis, married male, term extraction, query syntax, customer clusters, cluster profiles, prediction report, new varietal, cluster diagram, movie ratings, predictable state, address terms, web data, attribute profiles, model usage, field list, web applications, dry white, suggested threshold, attribute discrimination, data mining dimension, mining structure columns Key Phrases - Capitalized Phrases (CAPs): (learn more)
Analysis Services, Server Data Mining, Naïve Bayes, Dev Studio, Marital Status, Microsoft Decision Trees, Microsoft Association Rules, Cancel Figure, Microsoft Neural Network, Table Analysis Tools, Miles Europe, Microsoft Time Series, Microsoft Clustering, Star Wars Episode, Microsoft Sequence Clustering, Goal Seek, Home Ownership, Server Management Studio, Miles Pacific, Microsoft Logistic Regression, Reporting Services, Fill From Example, Analyze Key Influencers, Server Integration Services, State of the Union Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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