Building the data warehouse (2nd ed.)
Building the data warehouse (2nd ed.)
The data warehouse and data mining
Communications of the ACM
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Efficient view maintenance at data warehouses
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Multidimensional Database Technology
Computer
Materialized View Selection for Multidimensional Datasets
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming and Delivering Data
Data Warehousing and Knowledge Discovery: 8th International Conference, DaWaK 2006, Krakow, Poland, September 4-8, 2006, Proceedings (Lecture Notes in Computer Science)
Oracle Database 10g Performance Tuning Tips & Techniques
Oracle Database 10g Performance Tuning Tips & Techniques
Building a Data Warehouse: With Examples in SQL Server
Building a Data Warehouse: With Examples in SQL Server
Database Systems: Design, Implementation, and Management
Database Systems: Design, Implementation, and Management
Preface: Special issue on construction informatics
Advanced Engineering Informatics
Advanced Engineering Informatics
Advanced Engineering Informatics
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Current buildings' performance assessment tools are deficient in their ability to integrate and process building monitoring data to generate actionable information that can assist in achieving a higher level of building performance. Therefore, this paper addresses this problem by proposing the design and implementation of a multi-dimensional data analysis concept for building monitoring data. Firstly, the development of the multi-dimensional performance data model is described based on data warehouse technology. Secondly, a dedicated graphical user interface is introduced bringing the benefits of the multi-dimensional model to different stakeholders. Finally, the advantages of multi-dimensional performance data management is demonstrated in a real life case study for on-site and e-service performance management.