Web Data Warehouses have been introduced to enable the analysis of integrated Web data. One of the main challenges in these systems is to deal with the volatile and dynamic nature of Web sources. In this work we address the effects of adding/removing/changing Web sources and data items to the Data Warehouse (DW) schema. By managing source evolution we mean the automatic propagation of these changes to the DW. The proposed approach is based on a wrapper/mediator architecture, which reduces the impact of Web source changes on the DW schema. This paper presents this architecture and analyses some selected evolution cases in the context of Web DW
Data warehouse systems integrate data from heterogeneous sources. These sources are autonomous in na...
Abstract. In heterogeneous data warehousing environments, autonomous data sources are integrated int...
A data warehouse is a collection of historical data exploited by decision-support applications. It c...
Web Data Warehouses have been introduced to enable the analysis of integrated Web data. One of the m...
There is a lot of information published on the Web that can be useful for decision-making. The work...
International audienceA Data warehouse (DW) is characterized by a complex architecture, designed in ...
Data warehouses created for dynamic scientific environments, such as genetics, face significant chal...
Mediators are a critical component of any data warehouse; they transform data from source formats to...
The Data Warehouse (DW) is characterized by complex architecture, specific modeling and design appro...
A Data warehouse (DW) is a repository designed for querying and analyzing data. The main aims of a D...
Mediators are a critical component of any data warehouse; they transform data from source formats to...
International audienceModeling and data warehousing have been considered, for more than one decade, ...
The paper presents a: a) brief overview and analysis of existing approaches to the data warehouse (D...
Data warehouses created for dynamic scientific environments, such as genetics, face significant chal...
Abstract. Data warehouses tend to evolve, because of changes in data sources and business requiremen...
Data warehouse systems integrate data from heterogeneous sources. These sources are autonomous in na...
Abstract. In heterogeneous data warehousing environments, autonomous data sources are integrated int...
A data warehouse is a collection of historical data exploited by decision-support applications. It c...
Web Data Warehouses have been introduced to enable the analysis of integrated Web data. One of the m...
There is a lot of information published on the Web that can be useful for decision-making. The work...
International audienceA Data warehouse (DW) is characterized by a complex architecture, designed in ...
Data warehouses created for dynamic scientific environments, such as genetics, face significant chal...
Mediators are a critical component of any data warehouse; they transform data from source formats to...
The Data Warehouse (DW) is characterized by complex architecture, specific modeling and design appro...
A Data warehouse (DW) is a repository designed for querying and analyzing data. The main aims of a D...
Mediators are a critical component of any data warehouse; they transform data from source formats to...
International audienceModeling and data warehousing have been considered, for more than one decade, ...
The paper presents a: a) brief overview and analysis of existing approaches to the data warehouse (D...
Data warehouses created for dynamic scientific environments, such as genetics, face significant chal...
Abstract. Data warehouses tend to evolve, because of changes in data sources and business requiremen...
Data warehouse systems integrate data from heterogeneous sources. These sources are autonomous in na...
Abstract. In heterogeneous data warehousing environments, autonomous data sources are integrated int...
A data warehouse is a collection of historical data exploited by decision-support applications. It c...