Data Mining with Microsoft SQL Server(TM) 2000 Technical Reference (IT Professional) (Paperback)

by Claude Seidman (Author) "Recently I spoke with the CEO and CIO of a major auto sales company about their databases..." (more)
Key Phrases: local mining model, new mining model, mining model role, Analysis Services, Creating Data-Mining Applications, Visual Basic (more...)

Editorial Reviews

Amazon.com Review
Your organizational database is only as good as the strategic data you can extract from it. Do customers who buy breakfast cereal typically buy bananas as well? Is there a correlation between rainfall in a particular region and the prevalence of a particular illness there? Data Mining with Microsoft SQL Server 2000 Technical Reference shows how to use Microsoft's analysis tools for large databases. Author Claude Seidman offers advice on the data-modeling engineering process as a whole, including designing strategies likely to yield meaningful results, designing data warehouses, growing decision trees, spotting clusters and anomalies in data, and automating mining processes with code.

Despite its designation as a reference, this book is largely a tutorial--you'll refer to it for advice on how to make Analysis Services do something in particular. Seidman uses a classic and effective tutorial technique, sticking with an example throughout the book and adding to previous examples as he explores additional aspects of Microsoft data mining. His illustration involves identifying edible mushrooms, based on a database of facts about known mushrooms, and he's combined how-to prose with screen shots and accumulated wisdom to great effect. If your organization has gone with Microsoft SQL Server 2000 for data storage, read this book for advice on knowledge extraction. --David Wall

Topics covered: Microsoft Analysis Services, including the proper use of Data Transformation Services (DTS), PivotTable Services, Decision Support Objects (DSO), and the Microsoft implementation of On-Line Analytical Processing (OLAP).

Product Description
With its state-of-the-art capabilities for rapidly processing and retrieving huge quantities of data, Microsoft SQL Server 2000 is quickly growing in popularity among large corporations. But learning how to take advantage of the powerful, built-in data-mining services in SQL Server to turn all that data into meaningful information takes time and effort. Data Mining with SQL Server 2000 Technical Reference is the ideal, in-depth reference guide for any database developer, administrator, or IT professional who needs comprehensive information about these powerful new data-mining services. In particular, it fully examines the data-warehousing architecture in SQL Server 2000 to show how to take full advantage of the data-mining services in this RDBMS. This is the only Microsoft-approved technical guide to the data mining services in SQL Server 2000.

Product Details

• Paperback: 400 pages
• Publisher: Microsoft Press; 1 edition (June 9, 2001)
• Language: English
• ISBN-10: 0735612714
• ISBN-13: 978-0735612716
• Product Dimensions: 9.6 x 7.6 x 1.3 inches
• Shipping Weight: 5.3 ounces (View shipping rates and policies)
• Average Customer Review: 3.1 out of 5 stars See all reviews (7 customer reviews)
• Amazon.com Sales Rank: #307,866 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

17 of 17 people found the following review helpful:

4.0 out of 5 stars Book is better than the product, August 3, 2001

By	Jerome Vost (New York, NY) - See all my reviews

I have to agree with one of the previous reviewers when he said that given the absence of practically *ANY* documentation provided by Microsoft, this book is your only real source of information about Microsoft's data mining product.

I'm a big fan of OLAP amd data mining which made me better appreciate the time the author took to lay the groundwork for the discipline of data mining. Unlike a previous reviewer, I think that the author shares lots of real-world evperience which you can see by the way he bring up problems (which I have encountered myself) that occur when moving from raw data to a data mining model. He also catches some glitches and unreported features in the product for you and shows you how to work around them.

The book is actually very complete considering that the data mining product put out by Microsoft is promising, but extremely rudimentary. It provides only two basic data mining algorithms and gives a very clumsy way to try to add other algorithms. Thankfully, the author discusses techniques and pitfalls of mining numerical data and even shows you how to use SQL Server 2000 to perform a regression analysis for that purpose.

I would have given this book five stars except for two points :

1: The mushroom database is a good illustration of the use of the decision tree algorithm, but I think it may have been good to include a more business-oriented example that would bring data mining closer to it's intended purpose.

2: I was a little disappointed not to see any explanation as to how to add your own algorithms to the data mining product. Even if doing so requires C++ experience, it would have been perfectly fine to include it in a separate chapter or in an appendix. I don't know why the author chose not to include it.

Byond that, I would definitely recommend this book if you need to use MS data mining. The book is well written, and considering the infancy of the product, it's also very complete. Besides, you have no other real resource out there!

11 of 11 people found the following review helpful:

5.0 out of 5 stars Working in a Data Mine, June 13, 2001

By	edna "llmorgan" (Coral Springs, FL United States) - See all my reviews

I always look for Seidman's contributions in SQL magazines and at conferences since he always has something interesting and innovative to say that is fuelled by his depth of knowledge of the subject. What's more he has a great knack of presenting complicated (and sometimes, let's face it, not very exciting) concepts in a way that makes them easy to understand and in contexts that anyone can relate to. In particular his style is reminiscient of Roger Sessions (Com+ and the Battle for the Middle Tier, etc) minus the cynicism but with equal enthusiasm. No book can be all things to all people, but this is an excellent introduction to the world of Data mining and the power behind SQL200's implementation of it. I would recommend it to anyone looking to discover those hidden trends and patterns in their data, exploit them and become their CFO's best friend.

8 of 9 people found the following review helpful:

2.0 out of 5 stars Good technical reference, July 12, 2001

By A Customer

A lot of the information found in this book should have already been in the online documentation. The lack of documentation for data mining under sql server 2000 makes this book the only usefull reference out there. But overall, the book is poorly organised, badly written and requires a lot more in-dept information in order to put data mining into practical use.

You will find some information on DTS, but there are much better books out there on the topic. You will find some sample code for using DSO, but this topic is only touched upon and the code is NOT explained very well. The most important chapters were very thin (programming data mining and data mining queries). After reading the book, you will have an introduction to data mining, but you won't be able to use it effectively.

The examples in the book have no commercial value and are completely worthless. There is no CDROM that contains the data the author is using, and the sample data on the web is different to the data in the book. You will also have to start with chapter 8 (DTS) to load the sample data before you can follow the examples in the book.

I was really looking forward to get a copy of this book, but now that I have a copy, I am very dissapointed. The contents of this book shows that the author has no real world experience on the topic or is not willing to share it.