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Das Common-Warehouse-Metamodell (CWM) ist eine XML-basierte Technologie zum Datenaustausch aus Quellen jeder Art, unabhängig von der Plattform des Anbieters. Geschrieben von den Autoren der CWM-Spezifikation, bietet Ihnen dieses Buch eine gut verständliche Einführung in das Thema. Erklärt wird, wie Geschäftsbereiche mit Hilfe von CWM effizienter arbeiten können und mit welchen praktischen Schritten man CWM plant, implementiert und einführt. Sie erhalten einen Überblick über die Architektur von CWM und sehen, wie die einzelnen Komponenten in existierende Datenbanken und Data-Warehouse-Architekturen integriert werden können. Mit zugehöriger Website.
Written by the authors of the Common Warehouse Metamodel (CWM)specification, this book is the official and authoritativedeveloper's guide Provides a comprehensive look at how to develop database anddata warehouse applications using the Common WarehouseMetamodel Covers the full development lifecycle including applicationdesign implementation, and deployment Companion Web site includes updates on the technology,descriptions of tools, and links to vendor sites
Information is a key factor in business today, and data warehousing has become a major activity in the development and management of information systems to support the proper flow of information. Unfortunately, the majority of information systems are based on structured information stored in organizational databases, which means that the company is isolated from the business environment by concentrating on their internal data sources only. It is therefore vital that organizations take advantage of external business information, which can be retrieved from Internet services and mechanically organized within the existing information structures. Such a continuously extending integrated collection of documents and data could facilitate decision-making processes in the organization. Filtering the Web to Feed Data Warehouses discusses areas such as: - how to use data warehouse for filtering Web content - how to retrieve relevant information from diverse sources on the Web - how to handle the time aspect - how to mechanically establish links among data warehouse structures and documents filtered from external sources - how to use collected information to increase corporate knowledge and gives a comprehensive example, illustrating the idea of supplying data warehouses with relevant information filtered from the Web.
Written by the authors of the Common Warehouse Metamodel (CWM) specification, this book is the official and authoritative developer's guide Provides a comprehensive look at how to develop database and data warehouse applications using the Common Warehouse Metamodel Covers the full development lifecycle including application design implementation, and deployment Companion Web site includes updates on the technology, descriptions of tools, and links to vendor sites
William Giovinazzo gives experienced database professionals practical guidance for every aspect of planning and deploying Web-based data warehouses -- and leveraging them for competitive advantage. Unlike previous books, The Web-Enabled Data Warehouse covers all the enabling technologies and analysis approaches you need to know about -- from XML to CRM, Java to customer profiling. Giovinazzo begins by introducing the compelling advantages of integrating business intelligence and data warehouses with Web technology. He reviews the business and technical contexts in which the Web-enabled data warehouse will operate; shows how to build and optimize data warehouse infrastructure, and presents in-depth coverage of key enabling technologies -- including Java, XML and XSL, LDAP directories, and WAP wireless development environments. In the book's final section, Giovinazzo introduces and explains powerful new analysis techniques that can dramatically improve your understanding of customers -- and shows how to integrate data warehouses with CRM and other enterprise systems so you can act on your knowledge far more quickly and efficiently. For every experienced database professional seeking to understand or deploy Web-based data warehouses.
Defining a formal domain ontology is considered a useful, not to say necessary step in almost every software project. This is because software deals with ideas rather than with self-evident physical artefacts. However, this development step is hardly ever done, as ontologies rely on well-defined and semantically powerful AI concepts such as description logics or rule-based systems, and most software engineers are unfamiliar with these. This book fills this gap by covering the subject of MDA application for ontology development on the Semantic Web. The writing is technical yet clear, and is illustrated with examples. The book is supported by a website.
* The heart of the book provides the complete set of models that will support most of an organization's core business functions, including universal meta models for enterprise-wide systems, business meta data and data stewardship, portfolio management, business rules, and XML, messaging, and transactions * Developers can directly adapt these models to their own businesses, saving countless hours of development time * Building effective meta data repositories is complicated and time-consuming, and few IT departments have the necessary expertise to do it right-which is why this book is sure to find a ready audience * Begins with a quick overview of the Meta Data Repository Environment and the business uses of meta data, then goes on to describe the technical architecture followed by the detailed models
Whether you are a software developer, systems architect, data analyst, or business analyst, if you want to take advantage of data mining in the development of advanced analytic applications, Java Data Mining, JDM, the new standard now implemented in core DBMS and data mining/analysis software, is a key solution component. This book is the essential guide to the usage of the JDM standard interface, written by contributors to the JDM standard. - Data mining introduction - an overview of data mining and the problems it can address across industries; JDM's place in strategic solutions to data mining-related problems - JDM essentials - concepts, design approach and design issues, with detailed code examples in Java; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects - JDM in practice - the use of JDM from vendor implementations and approaches to customer applications, integration, and usage; impact of data mining on IT infrastructure; a how-to guide for building applications that use the JDM API - Free, downloadable KJDM source code referenced in the book available here
This volume comprises papers from the following three workshops that were part of the complete program for the International Conference on Extending Database Technology (EDBT) held in Prague, Czech Republic, in March 2002: XML-Based Data Management (XMLDM) Second International Workshop on Multimedia Data and Document Engineering (MDDE) Young Researchers Workshop (YRWS) Together, the three workshops featured 48 high-quality papers selected from approximately 130 submissions. It was, therefore, difficult to decide on the papers that were to be accepted for presentation. We believe that the accepted papers substantially contribute to their particular fields of research. The workshops were an excellent basis for intense and highly fruitful discussions. The quality and quantity of papers show that the areas of interest for the workshops are highly active. A large number of excellent researchers are working in relevant fields producing research output that is not only of interest to other researchers but also for industry. The organizers and participants of the workshops were highly satisfied with the output. The high quality of the presenters and workshop participants contributed to the success of each workshop. The amazing environment of Prague and the location of the EDBT conference also contributed to the overall success. Last, but not least, our sincere thanks to the conference organizers – the organizing team was always willing to help and if there were things that did not work, assistance was quickly available.
Most of modern enterprises, institutions, and organizations rely on knowledge-based management systems. In these systems, knowledge is gained from data analysis. Today, knowledge-based management systems include data warehouses as their core components. Data integrated in a data warehouse are analyzed by the so-called On-Line Analytical Processing (OLAP) applications designed to discover trends, patterns of behavior, and anomalies as well as finding dependencies between data. Massive amounts of integrated data and the complexity of integrated data coming from many different sources make data integration and processing challenging. New Trends in Data Warehousing and Data Analysis brings together the most recent research and practical achievements in the DW and OLAP technologies. It provides an up-to-date bibliography of published works and the resource of research achievements. Finally, the book assists in the dissemination of knowledge in the field of advanced DW and OLAP.