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Fundamentals of Data Warehouses
 
 
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Fundamentals of Data Warehouses [Hardcover]

Matthias Jarke (Author), Maurizio Lenzerini (Author), Yannis Vassiliou (Author), Panos Vassiliadis (Author)

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Book Description

January 17, 2003
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.

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Data warehouses have captured the attention of practitioners and researchers alike. But the design and optimization of data warehouses remains an art rather than a science. This book presents the first comparative review of the state of the art and best current practice of data warehouses. It covers source and data integration, multidimensional aggregation, query optimization, update propagation, metadata management, quality assessment, and design optimization. Furthermore, it presents a conceptual framework by which the architecture and quality of data warehouse efforts can be assessed and improved using enriched metadata management combined with advanced techniques from databases, business modeling, and artificial intelligence. For researchers and database professionals in academia and industry, the book offers an excellent introduction to the issues of quality and metadata usage in the context of data warehouses. In the second edition, the significant advances of the state of the practice in the last three years are discussed and the conceptual framework is extended to a full methodology for data warehouse design, illustrated by several industrial case studies.

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Inside This Book (learn more)
First Sentence:
Figure 1 .2 gives a rough overview of the usual data warehouse components and their relationships. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
view usability problem, data warehouse schema, refreshment process, data warehouse quality, data warehouse construction, interschema assertions, warehouse refreshment, data warehouse components, data warehouse practice, source schemata, refreshment strategy, value list indexes, multidimensional aggregation, data warehouse queries, multidimensional data models, global data warehouse, data warehouse administrator, data staging area, data warehouse architecture, operational data sources, data warehouse model, refreshment activities, schema merging, schema conforming, logged sources
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Product Where Sales, Select Product, World Wide Web, Brief Description, Sales Year
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