Wintersalen Sale
 
 

Special Offers see all

Enter to WIN a $100 Credit

Subscribe to PowellsBooks.news
for a chance to win.
Privacy Policy

Tour our stores


    Recently Viewed clear list


    The Powell's Playlist | October 21, 2014

    Anne Rice: IMG The Powell’s Playlist: Anne Rice



    These are the songs that wake me up, take me out of my worries and anxieties, wash my brain cells, and send me to the keyboard to write with new... Continue »

    spacer
Qualifying orders ship free.
$33.00
Used Trade Paper
Ships in 1 to 3 days
Add to Wishlist
Qty Store Section
1 Beaverton COMP- DATA SQL

Data Mining with SQL Server 2005 (Tentative)

by

Data Mining with SQL Server 2005 (Tentative) Cover

 

Synopses & Reviews

Publisher Comments:

Your 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

Synopsis:

* Written by Microsoft's lead developers of SQL Server 2005 data mining technologies, this authoritative book is the only one of its kind to explain the new Microsoft data mining standard and cover the complete set of Microsoft data mining algorithms, such as decision trees, clustering, association rules, and time series

* The authors begin with a simple example of the data mining features of SQL Server 2005, then move on to provide an in-depth description of data mining components, focusing on OLE DB

* Timed to publish with the software release, the book provides code-level tutorials on how to use SQL Server 2005 to solve real-world business problems, including building a cross-sales

* Web application, forecasting using Excel, creating a targeted mailing campaign, and predicting Web usage

Synopsis:

Data Mining with SQL Server Yukon shows database analysts and developers how to use all of the new features of Microsoft SQL Server Yukon for data mining. The book begins with a jump-start chapter, showing a simple example of the data mining features of SQL Server Yukon. The authors then provide an under-the-hood description of the data mining components of SQL Server Yukon, focusing on OLE DB for Data Mining. They show how to use each of the major data mining algorithms supported by this Microsoft tool, including decision trees, clustering, association rules, and time series. The authors also cover mining OLAP databases, as well as programming using ADO and stored procedures. The last set of chapters provide in-depth examples of using Microsoft data mining to solve four common types of business analysis problems., including:

o Building a cross-sales Web application.

o Forecasting using Excel.

o Creating a targeted mailing campaign.

o Predicting Web usage.

The companion Website will include the complete sample code and data sets provided in the book.

About the Author

ZhaoHui Tang is a Lead Program Manager in the Microsoft SQL Server Data Mining team. Joining Microsoft in 1999, he has been working on designing the data mining features of SQL Server 2000 and SQL Server 2005. He has spoken in many academic and industrial conferences including VLDB, KDD, TechED, PASS, etc. He has published a number of articles for database and data mining journals. Prior to Microsoft, he worked as a researcher at INRIA and Prism lab in Paris and led a team performing data-mining projects at Sema Group. He got his Ph.D. from the University of Versailles, France in 1996.

Jamie MacLennan is the Development Lead for the Data Mining Engine in SQL Server. He has been designing and implementing data mining functionality in collaboration with Microsoft Research since he joined Microsoft in 1999. In addition to developing the product, he regularly speaks on data mining at conferences worldwide, writes papers and articles about SQL Server Data Mining, and maintains data mining community sites. Prior to joining Microsoft, Jamie worked at Landmark Graphics, Inc. (division of Halliburton) on oil & gas exploration software and at Micrografx, Inc. on flowcharting and presentation graphics software. He studied undergraduate computer science at Cornell University.

Table of Contents

About the Authors.

Credits.

Foreword.

Chapter 1: Introduction to Data Mining.

Chapter 2: OLE DB for Data Mining.

Chapter 3: Using SQL Server Data Mining.

Chapter 4: Microsoft Naïve Bayes.

Chapter 5: Microsoft Decision Trees.

Chapter 6: Microsoft Time Series.

Chapter 7: Microsoft Clustering.

Chapter 8: Microsoft Sequence Clustering.

Chapter 9: Microsoft Association Rules.

Chapter 10: Microsoft Neural Network.

Chapter 11: Mining OLAP Cubes.

Chapter 12: Data Mining with SQL Server Integration Services.

Chapter 13: SQL Server Data Mining Architecture.

Chapter 14: Programming SQL Server Data Mining.

Chapter 15: Implementing a Web Cross-Selling Application.

Chapter 16: Advanced Forecasting Using Microsoft Excel.

Chapter 17: Extending SQL Server Data Mining.

Chapter 18: Conclusion and Additional Resources.

Appendix A: Importing Datasets.

Appendix B: Supported VBA and Excel Functions.

Index.

Product Details

ISBN:
9780471462613
Author:
Tang, Zhaohui
Publisher:
Wiley
Author:
MacLennan, Jamie
Subject:
Database Management - General
Subject:
Data mining
Subject:
Database design
Subject:
Database & Data Warehousing Technologies
Copyright:
Edition Description:
WebSite Associated w/Book
Publication Date:
20080505
Binding:
Electronic book text in proprietary or open standard format
Grade Level:
General/trade
Language:
English
Illustrations:
Y
Pages:
460
Dimensions:
233.7 x 188 x 25.4 mm 24 oz

Other books you might like

  1. Advanced Quantitative Techniques in... New Hardcover $133.40

Related Subjects

Computers and Internet » Database » Applications
Computers and Internet » Database » Design
Computers and Internet » Database » SQL
Computers and Internet » Software Engineering » Software Management
History and Social Science » Politics » General

Data Mining with SQL Server 2005 (Tentative) Used Trade Paper
0 stars - 0 reviews
$33.00 In Stock
Product details 460 pages John Wiley & Sons - English 9780471462613 Reviews:
"Synopsis" by , * Written by Microsoft's lead developers of SQL Server 2005 data mining technologies, this authoritative book is the only one of its kind to explain the new Microsoft data mining standard and cover the complete set of Microsoft data mining algorithms, such as decision trees, clustering, association rules, and time series

* The authors begin with a simple example of the data mining features of SQL Server 2005, then move on to provide an in-depth description of data mining components, focusing on OLE DB

* Timed to publish with the software release, the book provides code-level tutorials on how to use SQL Server 2005 to solve real-world business problems, including building a cross-sales

* Web application, forecasting using Excel, creating a targeted mailing campaign, and predicting Web usage

"Synopsis" by , Data Mining with SQL Server Yukon shows database analysts and developers how to use all of the new features of Microsoft SQL Server Yukon for data mining. The book begins with a jump-start chapter, showing a simple example of the data mining features of SQL Server Yukon. The authors then provide an under-the-hood description of the data mining components of SQL Server Yukon, focusing on OLE DB for Data Mining. They show how to use each of the major data mining algorithms supported by this Microsoft tool, including decision trees, clustering, association rules, and time series. The authors also cover mining OLAP databases, as well as programming using ADO and stored procedures. The last set of chapters provide in-depth examples of using Microsoft data mining to solve four common types of business analysis problems., including:

o Building a cross-sales Web application.

o Forecasting using Excel.

o Creating a targeted mailing campaign.

o Predicting Web usage.

The companion Website will include the complete sample code and data sets provided in the book.

spacer
spacer
  • back to top

FOLLOW US ON...

     
Powell's City of Books is an independent bookstore in Portland, Oregon, that fills a whole city block with more than a million new, used, and out of print books. Shop those shelves — plus literally millions more books, DVDs, and gifts — here at Powells.com.