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Download Microsoft Data Mining: Integrated Business Intelligence for e-Commerce and Knowledge Management djvu

Download Microsoft Data Mining: Integrated Business Intelligence for e-Commerce and Knowledge Management djvu

by Barry de Ville

Author: Barry de Ville
Subcategory: Programming
Language: English
Publisher: Digital Press; 1 edition (May 1, 2001)
Pages: 320 pages
Category: Technologies and Computers
Rating: 4.2
Other formats: docx mobi doc azw

Microsoft Data Mining approaches data mining from the particular perspective of IT professionals using Microsoft data management . It is becoming a foundation for e-commerce and knowledge management.

Microsoft Data Mining approaches data mining from the particular perspective of IT professionals using Microsoft data management technologies. The author explains the new data mining capabilities in Microsoft's SQL Server 2000 database, Commerce Server, and other products, details the Microsoft OLE DB for Data Mining standard, and gives readers best practices for using all of them.

Microsoft Data Mining approaches data mining from the particular . To the seasoned data mining professional, there are many other books on data mining that I would recommend before this one. The author explains the new data mining capabilities in Microsoft's SQL Server 2000 database. PhD, Data mining pioneer and consultant with the SAS Institute.

Microsoft Data Mining : Integrated Business Intelligence for e-Commerce and Knowledge Management. Microsoft Data Mining approaches data mining from the particular perspective of IT professionals using Microsoft data management technologies.

Learn more about Microsoft Data Mining Integrated Business Intelligence for e-Commerce and Knowledge Management on GlobalSpec. Microsoft Data Mining: Integrated Business Intelligence for e-Commerce and Knowledge Management. This book offers in-depth coverage of data mining using Microsoft data management technologies. Microsoft Data Mining Integrated Business Intelligence for e-Commerce and Knowledge Management.

Microsoft Data Mining: Integrated Business Intelligence for e-Commerce and Knowledge Management. Business Intelligence for the Enterprise. 6 Mb.

Document Warehousing and Text Mining: Techniques for Improving Business Operations, Marketing, and Sales.

Sullivan, Dan. Document Warehousing and Text Mining: Techniques for Improving Business Operations, Marketing, and Sales. New York: John Wiley & Sons, 2001. Collaboration and Communities. Cohen, Don, and Laurence Prusak. Boston, MA: Harvard Business School Publishing, 2001. Davenport, Thomas . and Laurence Prusak. Boston, MA: Harvard Business School Publishing,.

Introduction to Data Mining The Data Mining Process Data Mining Tools and Techniques Managing the Data Mining Project Modeling Data Deploying . Decision Tree for Business Intelligence and Data Mining.

Introduction to Data Mining The Data Mining Process Data Mining Tools and Techniques Managing the Data Mining Project Modeling Data Deploying the Results The Discovery and Delivery of Knowledge fo. More). How You Can Identify Influencers in SAS® Social Media Analysis (And Why It Matters). Don Hatcher, Gurpreet Singh Bawa, Barry de Ville. There are many ways to calculate influence in social media. Decision trees trace their origins to the era of the early development of written records.

Электронная книга "Decision Trees for Analytics Using SAS Enterprise Miner", Barry de Ville, Padraic Neville

Электронная книга "Decision Trees for Analytics Using SAS Enterprise Miner", Barry de Ville, Padraic Neville. Эту книгу можно прочитать в Google Play Книгах на компьютере, а также на устройствах Android и iOS. Выделяйте текст, добавляйте закладки и делайте заметки, скачав книгу "Decision Trees for Analytics Using SAS Enterprise Miner" для чтения в офлайн-режиме.

Microsoft Data Mining : Integrated Business Intelligence for e-Commerce and Knowledge Management, B. de Ville . de Ville ; pról. de Peter K. MacKinnon. Data warehouse : from architecture to implementation, B. Devlin. Incluye índice Incluye bibliografía. The most common previous uses of data mining have been to help businesses to gain and maintain a competitive advantage as well as to answer questions, solve problems, or make informed decisions. Although, more recentlyother industries have been turning to data mining to answer questions and solve problems.

Microsoft Data Mining approaches data mining from the particular perspective of IT professionals using Microsoft data management technologies. The author explains the new data mining capabilities in Microsoft's SQL Server 2000 database, Commerce Server, and other products, details the Microsoft OLE DB for Data Mining standard, and gives readers best practices for using all of them. The book bridges the previously specialized field of data mining with the new technologies and methods that are quickly making it an important mainstream tool for companies of all sizes.Data mining refers to a set of technologies and techniques by which IT professionals search large databases of information (such as those contained by SQL Server) for patterns and trends. Traditionally important in finance, telecommunication, and other information-intensive fields, data mining increasingly helps companies better understand and serve their customers by revealing buying patterns and related interests. It is becoming a foundation for e-commerce and knowledge management.Unique book on a hot data management topicPart of Digital Press's SQL Server and data mining clustersAuthor is an expert on both traditional and Microsoft data mining technologies