Data mining with Microsoft SQL server 2000 : technical reference.
Language: English
Published by Microsoft Press, Redmond, Wash, 2001
- Hardcover
- Used
Seller: Lost and Found Books, Healesville, VIC, AustraliaLost and Found Books
AbeBooks seller since June 20, 2000
Condition: Used - Very good
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Add to basketItem description from seller
Ill. ; 25 cm. Includes index. xiv, 367 pages VG. Light shelf and edge wear to covers, name on front endpaper, overall very good condition.
Seller Inventory # 16242
- Title
- Data mining with Microsoft SQL server 2000 : technical reference.
- Author
- Seidman, Claude
- Publisher
- Microsoft Press, Redmond, Wash
- Publication year
- 2001
- Condition
- Very good
- Dust jacket
- No Jacket
- Binding
- pictorial hard cover
- Language
- English
- ISBN 10
- 0735612714
- ISBN 13
- 9780735612716
- Seller catalogs
- engineering and technology
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
"Synopsis" may belong to another edition of this title.
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.
"About the title" may belong to another edition of this title.
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