Data Warehouses and OLAP: Concepts, Architectures and Solutions, 1st Edition

  • Published By:
  • ISBN-10: 1599043661
  • ISBN-13: 9781599043661
  • Grade Level Range: College Freshman - College Senior
  • 332 Pages | eBook
  • Original Copyright 2007 | Published/Released January 2007
  • This publication's content originally published in print form: 2007

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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.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Data Warehouses and OLAP: Concepts, Architectures and Solutions: Table of Contents.
1: Modeling and Designing.
2: Conceptual Modeling Solutions for the Data Warehouse.
3: Handling Structural Heterogeneity in OLAP.
4: Data Quality-Based Requirements Elicitation for Decision Support Systems.
5: Loading and Refreshing.
6: Extraction, Transformation, and Loading Processes.
7: Data Warehouse Refreshment.
8: Efficiency of Analytical Processing.
9: Advanced Ad Hoc Star Query Processing.
10: Bitmap Indices for Data Warehouses.
11: Indexing in Data Warehouses: Bitmaps and Beyond.
12: Efficient and Robust Node-Partitioned Data Warehouses.
13: OLAP with a Database Cluster.
14: Toward Integrating Data Warehousing with Data Mining Techniques.
15: Temporal Semistructured Data Models and Data Warehouses.
16: Spatial Online Analytical Processing (SOLAP): Concepts, Architectures, and Solutions from a Geomatics Engineering Perspective.
About the Editors.
About the Authors.