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Data Mining with Microsoft SQL Server 2008 (Anglais) Broché – 7 novembre 2008

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Présentation de l'éditeur

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.

Quatrième de couverture

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.

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Couverture | Copyright | Table des matières | Extrait | Index | Quatrième de couverture
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9 internautes sur 9 ont trouvé ce commentaire utile 
The authoritative resource on SQL Server 2008 Data Mining 3 février 2009
Par Elena Cristofor - Publié sur Amazon.com
Format: Broché
"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.
7 internautes sur 7 ont trouvé ce commentaire utile 
A plug-in developer must read 17 décembre 2008
Par Mnr R. Brits - Publié sur Amazon.com
Format: Broché
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 internautes sur 3 ont trouvé ce commentaire utile 
Get your hands dirty with SQL Server 2008 Data Mining Tools 9 mai 2009
Par Satyen@AmazonEU - Publié sur Amazon.com
Format: Broché
This is an excellent hands-on book on learning core concepts of data mining with SQL Server 2008. I have used this book as part of our Data Mining certification course at University Of Washington. The examples are very clear and their step-by-step approach really helped me in understanding various mining models and learning DMX query. Highly recommend for aspirant and experienced BI professionals.
4 internautes sur 5 ont trouvé ce commentaire utile 
Data Mining with Microsoft SQL Server 2008 5 décembre 2009
Par Patricia Carter - Publié sur Amazon.com
Format: Broché Achat vérifié
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.
1 internautes sur 1 ont trouvé ce commentaire utile 
The only reference on the subject 18 juin 2015
Par Dimitri Shvorob - Publié sur Amazon.com
Format: Broché
Sorry, this is not a five-star product. I am on page 104, and already

- The brief descriptions of data-mining tasks on pp. 6-10 are wobbly.
- Chapter 2's choice to delve into DMX syntax before a single walk-through exercise has been presented is unfortunate. It would have been so much better to introduce those operators and functions *in* the exercises, and maybe summarize in the end. One can easily fall asleep somewhere between p. 60 and p. 75.
- The database to be used for the exercise in Chapter 3 is found in the "Chapter 4" folder of the downloadable archive. The "Chapter 3" folder contains a completely different database.
- The writing just isn't good. Take pp. 104-105: the authors are meant to be walking through an exercise, but go off on a two-page tangent, leaving uncommented screenshots to guide the reader. [UPD: Oh, the steps are actually provided on pp. 107-108? Was I supposed to leaf ahead?]
- In Chapter 3, we are using a dataset of movie choices to predict number of bathrooms for home-owner individuals - and include all available variables in our model. The authors could not be bothered to come up with a sensible prediction challenge, or to think about the model?

Alas, this will have to do, as this seems to be the only book on SQL Server Data Mining. (I ignore the gnarled monstrosity published by Packt in 2014). And that is such a pity: an interesting, practical technology, clearly neglected by its creator.
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