Data Warehouses and OLAP: Concepts, Architectures, and Solutions
Data warehouses and online analytical processing (OLAP) are emerging key technologies for enterprise decision support systems. They provide sophisticated technologies from data integration, data collection and retrieval, query optimization, and data analysis to advanced user interfaces. New research and technological achievements in the area of data warehousing are implemented in commercial database management systems, and organizations are developing data warehouse systems into their information system infrastructures. Data Warehouses and OLAP: Concepts, Architectures and Solutions covers a wide range of technical, technological, and research issues. It provides theoretical frameworks, presents challenges and their possible solutions, and examines the latest empirical research findings in the area. It is a resource of possible solutions and technologies that can be applied when designing, implementing, and deploying a data warehouse, and assists in the dissemination of knowledge in this field.
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Conceptual Modeling Solutions for the Data Warehouse
Handling Structural Heterogeneity in OLAP
Data QualityBased Requirements Elicitation for Decision Support Systems
Loading and Refreshing
Extraction Transformation and Loading Processes
Data Warehouse Refreshment
Efficiency of Analytical Processing
Advanced Ad Hoc Star Query Processing
Efficient and Robust NodePartitioned Data Warehouses
OLAP with a Database Cluster
Toward Integrating Data Warehousing with Data Mining Techniques
Temporal Semistructured Data Models and Data Warehouses
Spatial Online Analytical Processing SOLAP Concepts Architectures and Solutions from a Geomatics Engineering Perspective
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About the Authors
Bitmap Indices for Data Warehouses
Indexing in Data Warehouses Bitmaps and Beyond
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Data Warehouses and OLAP: Concepts, Architectures and Solutions: Concepts ...
Ograniczony podgląd - 2006
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