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1 Beaverton COMP- DATA SQL

Other titles in the IT Professional series:

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

by

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

 

Out of Print

Synopses & Reviews

Publisher Comments:

The amount of information stored in corporate databases is exploding exponentially. Data mining—finding meaningful patterns in all that data—can give any organization a competitive advantage. This book is the in-depth reference from Microsoft for anyone who wants to take full advantage of the powerful data-mining features in SQL Server 2000. It examines the SQL Server 2000 Analysis Services architecture and shows how data mining fits into its complete suite of information-extraction technologies. Then it demonstrates how to structure and mine large databases with the algorithms included with SQL Server 2000 to find nuggets of useful information. It even shows how to create a practice data-mining model using data downloaded from a database. Coverage includes:

  • INTRODUCTION TO DATA MINING: What data mining is and isn’t, plus important principles and definitions behind data-mining methodologies, including the role of data-mining models, statistics, and algorithms
  • SQL SERVER 2000 ARCHITECTURE: How data mining fits into the SQL Server 2000 Analysis Services architecture and how it builds on the SQL Server 2000 relational database and its embedded online analytical processing (OLAP) engine
  • DATA-MINING METHODS: How to choose the best data-mining method for the job—decision trees or clustering
  • EASE OF USE FEATURES: How to use the Mining Model Wizard and the OLAP Mining Model Editor to simplify creating, training, and processing a model
  • PROGRAMMING THE DATA-MINING SERVICES: How to use data-mining models and Data Transformation Services, PivotTable Services, decision-support objects (DSO), PERL, Visual Basic, Scripting Edition, XML, and other tools and languages to work with the data-mining engine

Book News Annotation:

This guide to uncovering hidden information and meaningful patterns in large databases uses two sample databases to illustrate how to build a data-mining model. The author explains the SQL server analysis services architecture, data storage methods, how to create decision trees with online analytical processing (OLAP), the clustering method, data transformation services, decision support objects, the schema rowsets, data mining using PivotTable services, and prediction queries. An appendix discusses regression analysis.
Annotation c. Book News, Inc., Portland, OR (booknews.com)

Synopsis:

This guide to uncovering hidden information and meaningful patterns in large databases uses two sample databases to illustrate how to build a data-mining model. The author explains the SQL server analysis services architecture, data storage methods, how to create decision trees with online analytica

Synopsis:

This technical reference is the ideal, in-depth guide for any database developer, administrator, or IT professional who needs comprehensive information about these powerful new data-mining services. 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. (Computer Books - Database Management)

Synopsis:

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.

About the Author

Claude Seidman has been a software developer, DBA, and trainer since 1987 and has been using SQL Server since version 4.2. He specializes in SQL Server design and development as well as building decision support systems with Microsoft OLAP for use on the web. Claude has written articles in several publications, including SQL Server Magazine. He holds the MCSE, MCSD, MCDBA, MCP+I, and MCT certifications from Microsoft Magazine. Besides developing applications and administering databases, Claude teaches the MCSE track at a local university.

Table of Contents

AcknowledgmentsIntroductionIntroducing Data Mining
  • Chapter 1: Understanding Data Mining
  • Chapter 2: Microsoft SQL Server Analysis Services Architecture
  • Chapter 3: Data Storage Models
  • Chapter 4: Approaches to Data Mining
Data-Mining Methods
  • Chapter 5: Microsoft Decision Trees
  • Chapter 6: Creating Decision Trees with OLAP
  • Chapter 7: Microsoft Clustering
Creating Data-Mining Applications with Code
  • Chapter 8: Using Microsoft Data Transformation Services (DTS)
  • Chapter 9: Using Decision Support Objects (DSO)
  • Chapter 10: Understanding Data-Mining Structures
  • Chapter 11: Data Mining Using PivotTable Service
  • Chapter 12: Data-Mining Queries
Regression AnalysisGlossary of Data-Mining TermsAbout the Author

Product Details

ISBN:
9780735612716
Author:
Seidman, Claude
Publisher:
Microsoft Press
Author:
Microsoft Corporation, CJ
Author:
CJ Microsoft Corporation
Author:
Microsoft Corporation
Location:
Redmond, Wash.
Subject:
Programming - General
Subject:
Artificial Intelligence
Subject:
Database Management - General
Subject:
Database Management - Data Warehousing and Data Mining
Subject:
Data mining
Subject:
Database Management - SQL Server
Subject:
Sql server
Subject:
Database Management - Database Mining
Subject:
Database-SQL
Subject:
Computers-Reference - General
Copyright:
Edition Description:
Trade Paper
Series:
Developer Reference
Series Volume:
no. 21
Publication Date:
20010509
Binding:
Paperback
Language:
English
Illustrations:
Yes
Pages:
384
Dimensions:
9.03x7.69x.84 in. 1.45 lbs.

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Related Subjects

Computers and Internet » Computers Reference » General
Computers and Internet » Database » Applications
Computers and Internet » Database » SQL
Computers and Internet » Software Engineering » Programming and Languages
Religion » Comparative Religion » General
Science and Mathematics » Electricity » General Electronics
Science and Mathematics » Geology » General

Data Mining with Microsoft SQL Server 2000 Technical Reference (IT Professional) Used Hardcover
0 stars - 0 reviews
$6.50 In Stock
Product details 384 pages Microsoft Press - English 9780735612716 Reviews:
"Synopsis" by , This guide to uncovering hidden information and meaningful patterns in large databases uses two sample databases to illustrate how to build a data-mining model. The author explains the SQL server analysis services architecture, data storage methods, how to create decision trees with online analytica
"Synopsis" by ,
This technical reference is the ideal, in-depth guide for any database developer, administrator, or IT professional who needs comprehensive information about these powerful new data-mining services. 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. (Computer Books - Database Management)
"Synopsis" by , 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.
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