ePub Web Farming for the Data Warehouse (The Morgan Kaufmann Series in Data Management Systems) download
by Richard D. Hackathorn
In Web Farming for the Data Warehouse, author Richard D. Hackathorn applies his 30-plus years of information expertise to the novel concept of "Web farming. He lays out the methodology of cultivating the global Web for information relevant to an enterprise's operation. In the central portion of the book, the author explains the process of moving an organization to Web farming from both technological and managerial perspectives.
Download Web Farming for the Data Warehouse (The Morgan Kaufmann Series in Data Management Syste PDF. Michael Nez. Загрузка.
Web Farming is an exciting new area emerging out of data warehousing and web technology. It is defined as systematic business intelligence by farming the information resources of the Web. The objective is to enhance the contents of a data warehousing system. Data warehouses are usually based upon the contents of internal operations databases.
Start by marking Web Farming For The Data Warehouse as Want to. .
Start by marking Web Farming For The Data Warehouse as Want to Read: Want to Read savin. Hackathorn introduces a four-stage methodology and a growth strategy for the supporting architecture. This the first book to focus on the critical features of Web farming, is essential reading for anyone interested in the use of Web technology for data warehouse development, including corporate IT professionals, database administrators, and network administrators.
Get a full overview of The Morgan Kaufmann Series in Computer .
Get a full overview of The Morgan Kaufmann Series in Computer Architecture and Design Book Series. Most recent Volume: Computer Architecture. Turing Award recognizing contributions of lasting and major technical importance to the computing field, is fully revised with the latest developments in processor and system architecture. It also includes a new chapter on domain-specific architectures and an updated chapter on warehouse-scale computing that features the first public information on Google's newest WSC.
Richard T. Snodgrass Web Farming for the Data Warehouse Richard D. Hackathorn. Micheline Kamber Jian Pei Simon Fraser University. Amsterdam, boston, heidelberg, london new york, oxford, paris, san diego san francisco, singapore, sydney, tokyo. Morgan Kaufmann is an imprint of Elsevier. Morgan Kaufmann Publishers is an imprint of Elsevier. 225 Wyman Street, Waltham, MA 02451, USA c 2012 by Elsevier Inc. All rights reserved.
Web Farming for the Data Warehouse Richard D. This book can also be used by the advanced undergraduate or beginning graduate student to supplement a course textbook in introductory database management, or for a stand-alone course in data modeling or database design.
Hackathorn: Web Farming for the Data Warehouse (Morgan Kaufmann, 2000)Google Scholar. A. Maedche and S. Staab: Ontology Learning for the Semantic Web IEEE Intelligent Systems, 16(2) 72–79 (2001)CrossRefGoogle Scholar. 23. T. Nishida: Social Intelligence Design for the Web. IEEE Computer, 35(11) 37–41 (November 2002)Google Scholar. 24. M. Missikoff, R. Navigli, P. Velardi: Integrated Approach to Web Ontology Learning and Engineering, IEEE Computer, 35(11) 60–63 (November 2002)Google Scholar.
Web Farming is an exciting new area emerging out of data warehousing and web technology. It is defined as systematic business intelligence by farming the information resources of the Web. The objective is to enhance the contents of a data warehousing system. Data warehouses are usually based upon the contents of internal operations databases. With Web Farming, the focus can be balanced with external business factors, dealing moment by moment with global changes in the business environment.
Instead of surfing the Web haphazardly or gathering massive , Web Farming concentrates on an evolutionary process to systematically discover, acquire, structure, and disseminate content, constantly guided by business-critical intelligence to the enterprise. A four-stage methodology is suggested, along with growth strategy in the supporting architecture. Extensive coverage of standards, tools, and resources for Web Farming is given, along with an in-depth discussion of the important societal issues of privacy, confidentiality, intellectual property, and information espionage.
This is the first book that focuses on the critical features of Web Farming. This book will appeal to both a technical and business audience. The technical audience is anyone interested in the use of Web technology for data warehouse development, including corporate IT professionals, database administrators, network administrators, and all others who are responsible for data warehouse and data mining. The business audience is anyone interested in establishing effective business intelligence, such as strategic planners, business development managers, competitive intelligence analysts, and market researchers. * Discusses the issues surrounding the requirements and benefits of web farming in business, as well as the practical issues of software tools, techniques, and standards that provide a wealth of knowledge for the database professional* Provides a discussion of methodology and architecture required to successfully implement web-farming techniques* Includes access to author's resource center for web farming which is updated on a regular basis and provides links, references, reviews for relevant software and software tools, and colleague interaction.
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