Fundamentals of Data Warehouses
Nonfiction, Computers, Database Management, Information Storage & Retrievel, General Computing
| Author: | Matthias Jarke, Maurizio Lenzerini, Yannis Vassiliou, Panos Vassiliadis | ISBN: | 9783662041383 |
| Publisher: | Springer Berlin Heidelberg | Publication: | March 9, 2013 |
| Imprint: | Springer | Language: | English |
| Author: | Matthias Jarke, Maurizio Lenzerini, Yannis Vassiliou, Panos Vassiliadis |
| ISBN: | 9783662041383 |
| Publisher: | Springer Berlin Heidelberg |
| Publication: | March 9, 2013 |
| Imprint: | Springer |
| Language: | English |
The first comparative review of the state of the art and best current practice in data warehousing. It covers source and data integration, multidimensional aggregation, query optimisation, update propagation, metadata management, quality assessment, and design optimisation. Also, based on results of the European DWQ project, it offers a conceptual framework by which the architecture and quality of data warehousing efforts can be assessed and improved using enriched metadata management combined with advanced techniques from databases, business modelling, and artificial intelligence. An excellent introduction to the issues of quality and metadata usage for researchers and database professionals in academia and industry. XXXXXXX Neuer Text This book presents the first comparative review of the state-of-the-art and the best current practices of data warehouses. It covers source and data integration, multidimensional aggregation, query optimization, metadata management, quality assessment, and design optimization. A conceptual framework is presented by which the architecture and quality of a data warehouse can be assessed and improved using enriched metadata management combined with advanced techniques from databases, business modeling, and artificial intelligence.
The first comparative review of the state of the art and best current practice in data warehousing. It covers source and data integration, multidimensional aggregation, query optimisation, update propagation, metadata management, quality assessment, and design optimisation. Also, based on results of the European DWQ project, it offers a conceptual framework by which the architecture and quality of data warehousing efforts can be assessed and improved using enriched metadata management combined with advanced techniques from databases, business modelling, and artificial intelligence. An excellent introduction to the issues of quality and metadata usage for researchers and database professionals in academia and industry. XXXXXXX Neuer Text This book presents the first comparative review of the state-of-the-art and the best current practices of data warehouses. It covers source and data integration, multidimensional aggregation, query optimization, metadata management, quality assessment, and design optimization. A conceptual framework is presented by which the architecture and quality of a data warehouse can be assessed and improved using enriched metadata management combined with advanced techniques from databases, business modeling, and artificial intelligence.
