Data Warehousing and Knowledge Discovery 13th International Conference DaWaK 2011 Toulouse, France August 29 September 2 2011 Proceedings 1st Edition by Alfredo Cuzzocrea, Umeshwar Dayal ISBN 3540452281 9783540452287

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ISBN 10: 3540452281

ISBN 13: 9783540452287

Author: Alfredo Cuzzocrea, Umeshwar Dayal

Data Warehousing and Knowledge Discovery: 13th International Conference, DaWaK 2011, Toulouse, France, August 29- September 2, 2011, Proceedings 1st Edition: 

Data Warehousing and Knowledge Discovery: 13th International Conference, DaWaK 2011, Toulouse, France, August 29- September 2, 2011, Proceedings 1st Edition Table of contents:

Physical and Conceptual Data Warehouse Models

• A Predictable and Scalable DW Model
• The Planning OLAP Model – A Multidimensional Model with Planning Support
• Extending the Dimensional Templates Approach to Integrate Complex Multidimensional Design Concepts
• OLAP Formulations for Supporting Complex Spatial Objects in Data Warehouses

Data Warehousing Design Methodologies and Tools

• Multidimensional Database Design from Document-Centric XML Documents
• Modern Software Engineering Methodologies Meet Data Warehouse Design: 4WD
• GEM: Requirement-Driven Generation of ETL and Multidimensional Conceptual Designs

ETL Methodologies and Tools

• ETLMR: A Highly Scalable Dimensional ETL Framework Based on MapReduce
• Complementing Data in the ETL Process
• TTL: A Transformation, Transference and Loading Approach for Active Monitoring
• Support for User Involvement in Data Cleaning

Data Warehouse Performance and Optimization

• Efficient Processing of Drill-across Queries over Geographic Data Warehouses
• The NOX OLAP Query Model: From Algebra to Execution
• VarDB: High-Performance Warehouse Processing with Massive Ordering and Binary Search

Data Warehouse Partitioning Techniques

• Vertical Fragmentation of XML Data Warehouses Using Frequent Path Sets
• Implementing Vertical Splitting for Large Scale Multidimensional Datasets and Its Evaluations

Analytics over Large Multidimensional Datasets

• Describing Analytical Sessions Using a Multidimensional Algebra
• Tagged MapReduce: Efficiently Computing Multi-analytics Using MapReduce

Pattern Mining

• Frequent Pattern Mining from Time-Fading Streams of Uncertain Data
• ………………..

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