Fundamentals of Data Warehouses
Fundamentals of Data Warehouses
Modelling Ubiquitous Web Applications - The WUML Approach
Revised Papers from the HUMACS, DASWIS, ECOMO, and DAMA on ER 2001 Workshops
Computing appropriate representations for multidimensional data
Data & Knowledge Engineering - Special issue: Advances in OLAP
Personalized systems: models and methods from an IR and DB perspective
VLDB '05 Proceedings of the 31st international conference on Very large data bases
A personalization framework for OLAP queries
Proceedings of the 8th ACM international workshop on Data warehousing and OLAP
Research in data warehouse modeling and design: dead or alive?
DOLAP '06 Proceedings of the 9th ACM international workshop on Data warehousing and OLAP
A UML profile for multidimensional modeling in data warehouses
Data & Knowledge Engineering - Special issue: ER 2003
Foundations of preferences in database systems
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
OLAP preferences: a research agenda
Proceedings of the ACM tenth international workshop on Data warehousing and OLAP
Towards Comprehensive Requirement Analysis for Data Warehouses: Considering Security Requirements
ARES '08 Proceedings of the 2008 Third International Conference on Availability, Reliability and Security
Model-Driven Metadata for OLAP Cubes from the Conceptual Modelling of Data Warehouses
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Bridging the semantic gap in OLAP models: platform-independent queries
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
The Data Warehouse Lifecycle Toolkit
The Data Warehouse Lifecycle Toolkit
Modeling and storing context-aware preferences
ADBIS'06 Proceedings of the 10th East European conference on Advances in Databases and Information Systems
Using web-based personalization on spatial data warehouses
Proceedings of the 2010 EDBT/ICDT Workshops
A framework for OLAP content personalization
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
A personalization process for spatial data warehouse development
Decision Support Systems
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Data warehouses rely on multidimensional models in order to provide decision makers with appropriate structures to intuitively analyze data with OLAP technologies. However, data warehouses may be potentially large and multidimensional structures become increasingly complex to be understood at a glance. Even if a departmental data warehouse (also known as data mart) is used, these structures would be also too complex. As a consequence, acquiring the required information is more costly than expected and decision makers using OLAP tools may get frustrated. In this context, current approaches for data warehouse design are focused on deriving a unique OLAP schema for all analysts from their previously stated information requirements, which is not enough to lighten the complexity of the decision making process. To overcome this drawback, we argue for personalizing multidimensional models for OLAP technologies according to the continuously changing user characteristics, context, requirements and behaviour. In this paper, we present a novel approach to personalizing OLAP systems at the conceptual level based on the underlying multidimensional model of the data warehouse, a user model and a set of personalization rules. The great advantage of our approach is that a personalized OLAP schema is provided for each decision maker contributing to better satisfy their specific analysis needs. Finally, we show the applicability of our approach through a sample scenario based on our CASE tool for data warehouse development.