International Business Machines Corporation

Ruben Pulido De Los Reyes

Christoph H Sieb

Michael Wurst

Alexander Lang

Bernhard Mitschang

A Business Intelligence (BI) meta model template is selected based on one or more meta model object types in a model structure. A BI meta model is generated from the selected BI meta model template. One or more BI report specification templates are selected based on a mining model type. A BI report specification is generated from the selected one or more BI report specification templates, a schema of the model structure, and content of the model structure. The BI meta model and the BI report specification are deployed to a BI server for use in generating a BI report using a BI tool at the BI server. In response to a user request for a BI report, the BI report is generated with a BI tool at the BI server that uses the BI meta model and the BI report specification.

Deployment of a business intelligence (BI) meta model and a BI report specification for use in presenting data mining and predictive insights using BI tools

A new data mining model (DMM) is created having at least one of the following characteristics: quality and complexity. The new DMM is handled as a candidate for storing in a storage device if a predefined criterion for the characteristics is met. The sum of the sizes of the new DMM and already stored DMMs is determined. In response to the sum falling below a storage limit, the new DMM is stored in the storage device. In response to the sum exceeding the storage limit, a decision is taken based on priorities of the DMMs which DMMs to store in the storage device.

Selective storing of mining models for enabling interactive data mining

Computerized methods, data processing systems, and computer program products for storing of data mining models (DMMs) are provided. A new DMM is created having at least one of the following characteristics: quality and complexity. The new DMM is handled as a candidate for storing in a storage device if a predefined criterion for the characteristics is met. The sum of the sizes of the new DMM and already stored DMMs is determined. In response to the sum falling below a storage limit, the new DMM is stored in the storage device. In response to the sum exceeding the storage limit, a decision is taken based on priorities of the DMMs which DMMs to store in the storage device. The priorities depend at least on access frequencies of the DMMs. Upon a data mining request, a corresponding DMM is determined and a user is requested to confirm that data mining is to proceed if quality of the determined DMM does not fulfill a further predefined criterion.

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Stuttgart, Germany

Ruben Pulido De Los Reyes