Catálogo de publicaciones - libros

Several business intelligence concepts show that it is possible to build a data warehouse based on heterogeneous quantitative and qualitative data. But the danger of flooding the management with information still remains. Business information should be made available according to the personal need of a manager by a self-defined push mechanism. The concept of active data warehousing is going to be expanded in this way, first. Messages about new relevant information should be created for quantitative and qualitative data as well. Due to this, there is a need for an enterprise specific ontology. This ontology works as an intermediate between current information and user profiles. Just interesting information are passed to the user. The second approach clusters qualitative data in favour of visualization. The usage of increasing cell structures provides a self organizing map. Decision makers will get the opportunity to search in document volumes, which are clustered.

Several business intelligence concepts show that it is possible to build a data warehouse based on heterogeneous quantitative and qualitative data. But the danger of flooding the management with information still remains. Business information should be made available according to the personal need of a manager by a self-defined push mechanism. The concept of active data warehousing is going to be expanded in this way, first. Messages about new relevant information should be created for quantitative and qualitative data as well. Due to this, there is a need for an enterprise specific ontology. This ontology works as an intermediate between current information and user profiles. Just interesting information are passed to the user. The second approach clusters qualitative data in favour of visualization. The usage of increasing cell structures provides a self organizing map. Decision makers will get the opportunity to search in document volumes, which are clustered.

Several business intelligence concepts show that it is possible to build a data warehouse based on heterogeneous quantitative and qualitative data. But the danger of flooding the management with information still remains. Business information should be made available according to the personal need of a manager by a self-defined push mechanism. The concept of active data warehousing is going to be expanded in this way, first. Messages about new relevant information should be created for quantitative and qualitative data as well. Due to this, there is a need for an enterprise specific ontology. This ontology works as an intermediate between current information and user profiles. Just interesting information are passed to the user. The second approach clusters qualitative data in favour of visualization. The usage of increasing cell structures provides a self organizing map. Decision makers will get the opportunity to search in document volumes, which are clustered.

Several business intelligence concepts show that it is possible to build a data warehouse based on heterogeneous quantitative and qualitative data. But the danger of flooding the management with information still remains. Business information should be made available according to the personal need of a manager by a self-defined push mechanism. The concept of active data warehousing is going to be expanded in this way, first. Messages about new relevant information should be created for quantitative and qualitative data as well. Due to this, there is a need for an enterprise specific ontology. This ontology works as an intermediate between current information and user profiles. Just interesting information are passed to the user. The second approach clusters qualitative data in favour of visualization. The usage of increasing cell structures provides a self organizing map. Decision makers will get the opportunity to search in document volumes, which are clustered.

Several business intelligence concepts show that it is possible to build a data warehouse based on heterogeneous quantitative and qualitative data. But the danger of flooding the management with information still remains. Business information should be made available according to the personal need of a manager by a self-defined push mechanism. The concept of active data warehousing is going to be expanded in this way, first. Messages about new relevant information should be created for quantitative and qualitative data as well. Due to this, there is a need for an enterprise specific ontology. This ontology works as an intermediate between current information and user profiles. Just interesting information are passed to the user. The second approach clusters qualitative data in favour of visualization. The usage of increasing cell structures provides a self organizing map. Decision makers will get the opportunity to search in document volumes, which are clustered.

Several business intelligence concepts show that it is possible to build a data warehouse based on heterogeneous quantitative and qualitative data. But the danger of flooding the management with information still remains. Business information should be made available according to the personal need of a manager by a self-defined push mechanism. The concept of active data warehousing is going to be expanded in this way, first. Messages about new relevant information should be created for quantitative and qualitative data as well. Due to this, there is a need for an enterprise specific ontology. This ontology works as an intermediate between current information and user profiles. Just interesting information are passed to the user. The second approach clusters qualitative data in favour of visualization. The usage of increasing cell structures provides a self organizing map. Decision makers will get the opportunity to search in document volumes, which are clustered.

Several business intelligence concepts show that it is possible to build a data warehouse based on heterogeneous quantitative and qualitative data. But the danger of flooding the management with information still remains. Business information should be made available according to the personal need of a manager by a self-defined push mechanism. The concept of active data warehousing is going to be expanded in this way, first. Messages about new relevant information should be created for quantitative and qualitative data as well. Due to this, there is a need for an enterprise specific ontology. This ontology works as an intermediate between current information and user profiles. Just interesting information are passed to the user. The second approach clusters qualitative data in favour of visualization. The usage of increasing cell structures provides a self organizing map. Decision makers will get the opportunity to search in document volumes, which are clustered.

Several business intelligence concepts show that it is possible to build a data warehouse based on heterogeneous quantitative and qualitative data. But the danger of flooding the management with information still remains. Business information should be made available according to the personal need of a manager by a self-defined push mechanism. The concept of active data warehousing is going to be expanded in this way, first. Messages about new relevant information should be created for quantitative and qualitative data as well. Due to this, there is a need for an enterprise specific ontology. This ontology works as an intermediate between current information and user profiles. Just interesting information are passed to the user. The second approach clusters qualitative data in favour of visualization. The usage of increasing cell structures provides a self organizing map. Decision makers will get the opportunity to search in document volumes, which are clustered.

Several business intelligence concepts show that it is possible to build a data warehouse based on heterogeneous quantitative and qualitative data. But the danger of flooding the management with information still remains. Business information should be made available according to the personal need of a manager by a self-defined push mechanism. The concept of active data warehousing is going to be expanded in this way, first. Messages about new relevant information should be created for quantitative and qualitative data as well. Due to this, there is a need for an enterprise specific ontology. This ontology works as an intermediate between current information and user profiles. Just interesting information are passed to the user. The second approach clusters qualitative data in favour of visualization. The usage of increasing cell structures provides a self organizing map. Decision makers will get the opportunity to search in document volumes, which are clustered.

Several business intelligence concepts show that it is possible to build a data warehouse based on heterogeneous quantitative and qualitative data. But the danger of flooding the management with information still remains. Business information should be made available according to the personal need of a manager by a self-defined push mechanism. The concept of active data warehousing is going to be expanded in this way, first. Messages about new relevant information should be created for quantitative and qualitative data as well. Due to this, there is a need for an enterprise specific ontology. This ontology works as an intermediate between current information and user profiles. Just interesting information are passed to the user. The second approach clusters qualitative data in favour of visualization. The usage of increasing cell structures provides a self organizing map. Decision makers will get the opportunity to search in document volumes, which are clustered.