Product DescriptionYour in-depth guide to using the new Microsoft data mining standard to solve today's business problems
Concealed inside your data warehouse and data marts is a wealth of valuable information just waiting to be discovered. All you need are the right tools to extract that information and put it to use. Serving as your expert guide, this book shows you how to create and implement data mining applications that will find the hidden patterns from your historical datasets. The authors explore the core concepts of data mining as well as the latest trends. They then reveal the best practices in the field, utilizing the innovative features of SQL Server 2005 so that you can begin building your own successful data mining projects.
You'll learn:
The principal concepts of data mining
How to work with the data mining algorithms included in SQL Server data mining
How to use DMX-the data mining query language
The XML for Analysis API
The architecture of the SQL Server 2005 data mining component
How to extend the SQL Server 2005 data mining platform by plugging in your own algorithms
How to implement a data mining project using SQL Server Integration Services
How to mine an OLAP cube
How to build an online retail site with cross-selling features
How to access SQL Server 2005 data mining features programmatically
Customer Reviews
Average Rating:
Rating: - Theory-oriented book
1) The book uses many examples based on the AllElectronics database. However, the book does not provide the AllElectronics database. Nowhere on the net where you can download AllElectronics database, even on the publisher website. This book is supposed to show us how to design and run data mining on SQL Server 2005, but it fails to do that since the examples in the book are not runnable. I've read many books about Data Mining for SQL 2005. All of them have runnable code except this book.
... Read More
Rating: - Superficial almost to the point of uselessness
I bought this book specifically to gain insight into the output I've gotten from using a couple of the data mining algorithms; unfortunately, there's even less on output interpretation than there is in the SQL server help files. Flipping through the book leaves the impression that the authors are trying to be everything to everyone, and end up only scratching the surface except in describing the algorithms.
I would have given it a 3 star rating anyway because it is useful to understand ... Read More
Rating: - Just what I needed!
I have only recently started to get involved with Data Mining. I have been doing back end work with Analysis Services for a couple of years and we're ready to move on to the next level.
This book was amazing! The background in Analysis Services and Databases helped a lot, but the book covered all the topics in an easy to understand order. Sure, the chapters on the different algorithms can be very in depth, but apart from explaining the actual mathematical formulas, there is a huge amount ... Read More
Rating: - Great Book for All Levels
I was really impressed with this book. It had a great introduction to demystify the typic of data mining. Since the learning curve on this topic is so high, these first few chapters are essential. It then immediately jumps into a practical example to help the reader bring it all together. The chapters get progressivily more difficult through the book and there's a chapter for each of the algorithms. The author team did a fantastic job and I'd highly recommend it.
Rating: - A bible for those using SQL 2005
Some people commented on the poor editing: typos & some wrong pictures. True. (It detracts, but you can figure it out easily)
Some stated that it is not a good general overview of Data Mining. True (though it has a bit of a summary)
Some stated that is doesn't discuss business applications in detail. Yes, (it only makes brief reference to them).
Some stated that it is very vendor specific. Hello, read the title - SQL 2005.
It is a must read for anyone who wants to take ... Read More
- Theory-oriented book
- Superficial almost to the point of uselessness
- Just what I needed!
