This book by Jamie MacLennan, ZhaoHui Tang and Bogdan Crivat (all developers of the product in Redmond) is a very practical guide and quite readable by someone new to data mining. It starts with the data mining tools included in Excel 2007 and goes on to detail all the algorithms, the syntax of the DMX language and embedding data mining in your applications. Experienced data mining will also find the book useful. I found many useful tips. For example, I only just learnt that you can nest MDX in your DMX queries. It is more common to embed SQL in data mining queries.
To learn about data mining, I really believe that you need some real data to explore. The book has a download site where readers can download databases and demonstrations to experiment with.
If you are using Analysis Services and haven't yet started data mining, I suggest that you get a copy of this book and teach yourself data mining. Data mining is going to be really big.
I did have trouble with Wiley download url, but here is a direct link for the exercise data. http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470277742,descCd-DOWNLOAD.html
By the way, for anyone who is interested, there are a couple of live data mining demonstrations on my site. Where data mining is embedded in Reporting Services (also covered in the book). There is a book suggestion tool using the library data I mentioned above, and the another that predicts response times for the last 50 http requests on my web server. This demonstration has no practical value, but hopefully you can draw the analogy to a similar model that predicts customer profitability etc. http://RichardLees.com.au/sites/Demonstrations/Pages/LibrariesSuggestions.aspxRichard