Data mining with Microsoft SQL server 2000 : technical reference

Başlık:

Yazar:

Seidman, Claude, 1964-

ISBN:

9780735612716

Ek Yazar:

Seidman, Claude, 1964-

Yayım Bilgisi:

Fiziksel Tanım:

xiv, 367 pages : illustrations ; 25 cm

General Note:

Includes index.

Contents:

Understanding Data Mining -- Microsoft SQL Server Analysis Services Architecture -- Data Storage Models -- Approaches to Data Mining -- Microsoft Decision Trees -- Creating Decision Trees with OLAP -- Microsoft Clustering -- Using Microsoft Data Transformation Services (DTS) -- Using Decision Support Objects (DSO) -- Understanding Data-Mining Structures -- Data Mining Using PivotTable Service -- Data-Mining Queries.

Title Subject:

SQL server.

Konu Terimleri:

Data mining.

Veri madenciliği.

Mevcut:*

Library	Materyal Türü	Barkod	Yer Numarası	Durum
Searching... Pamukkale Merkez Kütüphanesi	Kitap	0050243	QA76.9 .D343 S45 2001	Searching... Unknown

Bound With These Titles

On Order

Özet

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

Author Notes

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.