Abstract: Embodiments of a system and method are disclosed concerning the management of a plurality input methods on a computer. The input method may define how input from a human interface device is interpreted by a receiving application. The method may include locating one or more input method factors. The method may also include determining a numerical score of the input method factor using a metric of the input method factor and a weight of the factor. The method may also include ranking an input method factor using the determined numerical score of the input method factor. The method may also include presenting a user selection interface that lists the plurality of input methods as a function of the ranking.

Abstract: Embodiments of a system and method are disclosed concerning the management of a plurality input methods on a computer. The input method may define how input from a human interface device is interpreted by a receiving application. The method may include locating one or more input method factors. The method may also include determining a numerical score of the input method factor using a metric of the input method factor and a weight of the factor. The method may also include ranking an input method factor using the determined numerical score of the input method factor. The method may also include presenting a user selection interface that lists the plurality of input methods as a function of the ranking.

Abstract: Embodiments of a system and method are disclosed concerning the management of a plurality input methods on a computer. The input method may define how input from a human interface device is interpreted by a receiving application. The method may include locating one or more input method factors. The method may also include determining a numerical score of the input method factor using a metric of the input method factor and a weight of the factor. The method may also include ranking an input method factor using the determined numerical score of the input method factor. The method may also include presenting a user selection interface that lists the plurality of input methods as a function of the ranking.

Abstract: Embodiments of a system and method are disclosed concerning the management of a plurality input methods on a computer. The input method may define how input from a human interface device is interpreted by a receiving application. The method may include locating one or more input method factors. The method may also include determining a numerical score of the input method factor using a metric of the input method factor and a weight of the factor. The method may also include ranking an input method factor using the determined numerical score of the input method factor. The method may also include presenting a user selection interface that lists the plurality of input methods as a function of the ranking.

Abstract: A set of command tags and associated command instructions are provided along with a driver mechanism for converting ETL instructions from a first set of ETL instructions to a second set of ETL instructions. With the system and method, the command tags may be used with a first set of ETL instructions to indicate the manner by which these ETL instructions are to be executed. The tags are identified by the driver mechanism and associated with one or more command instructions. The command instructions are loaded along with the first set of ETL instructions by the driver mechanism. The driver mechanism converts the first set of ETL instructions into a second set of ETL instructions based on the command instructions associated with the identified tags. The second set of ETL instructions are performed as a plurality of transactions rather than a single transaction.

Abstract: Providing flexibility in scheduling control for an extract, transfer, and load (“ETL”) scheduler in a data warehouse system, including extracting from a computer memory of the data warehouse system a dependent condition for a scheduled ETL processing step of the ETL scheduler, extracting from computer memory related ETL data for the dependent condition, determining whether the ETL data satisfies the dependent condition, and executing the scheduled step if the ETL data satisfies the dependent condition. A sub-scheduler typically is implemented as an interface between an ETL scheduler and external programs without modification of the ETL scheduler. In typical embodiments, an ETL scheduler includes a multiplicity of scheduled ETL processing steps, and computer memory of a data warehouse system includes dependent conditions for at least one of the scheduled ETL processing steps and ETL data related to at least one dependent condition.

Abstract: Managing data mining activities in a data mining environment, including selecting a model scoring results table, wherein the selecting is carried out in dependence upon metadata included in a model scoring results control table, the model scoring results control table being related to a data set control table including data set metadata; reading a scoring output data record from the selected model scoring results table; storing the scoring output data record in a managed representation table for scoring results; selecting a model training results file, wherein the selecting is carried out in dependence upon metadata included in a mining model control table; reading training results data from the selected model training results file; and storing the training results data in a model training results table, the model training results table comprising a relational representation of the training results data from the selected model training results file.

Abstract: Exemplary embodiments typically include methods of deploying a predefined data warehouse process model from a development system having a development environment to a customer system having a customer environment, the customer environment being different from the development environment. Embodiments typically include exporting metadata from the predefined warehouse process model to an interchange metadata file, in which the metadata comprises data elements describing a development environment, in which the metadata comprises at least some data elements having values that are site dependent, and copying, from the interchange metadata file to an interchange resource file, site dependent data elements. Embodiments typically include identifying site dependent data values of the customer system, converting in the interchange metadata file, the site dependent data element values to the site dependent data values of the customer system, and importing the interchange metadata file into the customer system.

Abstract: A set of command tags and associated command instructions are provided along with a driver mechanism for converting ETL instructions from a first set of ETL instructions to a second set of ETL instructions. With the system and method, the command tags may be used with a first set of ETL instructions to indicate the manner by which these ETL instructions are to be executed. The tags are identified by the driver mechanism and associated with one or more command instructions. The command instructions are loaded along with the first set of ETL instructions by the driver mechanism. The driver mechanism converts the first set of ETL instructions into a second set of ETL instructions based on the command instructions associated with the identified tags. The second set of ETL instructions are performed as a plurality of transactions rather than a single transaction.

Abstract: Managing a data mining environment, the data mining environment having a data mining tool and a data mining model. Embodiments include registering in a data set control table registered data sets, the registered data sets including the model training input data sets, model training results data sets, the scoring input data sets, and the scoring output data sets, registering the data mining model in a mining model control table, the mining model control table being related to the data set control table through a mining model control table foreign key, and registering the scoring output data sets in a scoring control table, the scoring control table being related to the data set control table through a scoring control table data set foreign key, the scoring control table being related to the mining model control table through a scoring control table mining model foreign key.

Abstract: Providing flexibility in scheduling control for an extract, transfer, and load (“ETL”) scheduler in a data warehouse system, including extracting from a computer memory of the data warehouse system a dependent condition for a scheduled ETL processing step of the ETL scheduler, extracting from computer memory related ETL data for the dependent condition, determining whether the ETL data satisfies the dependent condition, and executing the scheduled step if the ETL data satisfies the dependent condition. A sub-scheduler typically is implemented as an interface between an ETL scheduler and external programs without modification of the ETL scheduler. In typical embodiments, an ETL scheduler includes a multiplicity of scheduled ETL processing steps, and computer memory of a data warehouse system includes dependent conditions for at least one of the scheduled ETL processing steps and ETL data related to at least one dependent condition.

Abstract: Managing data mining activities in a data mining environment, including selecting a model scoring results table, wherein the selecting is carried out in dependence upon metadata included in a model scoring results control table, the model scoring results control table being related to a data set control table including data set metadata; reading a scoring output data record from the selected model scoring results table; storing the scoring output data record in a managed representation table for scoring results; selecting a model training results file, wherein the selecting is carried out in dependence upon metadata included in a mining model control table; reading training results data from the selected model training results file; and storing the training results data in a model training results table, the model training results table comprising a relational representation of the training results data from the selected model training results file.

Abstract: Managing model scoring results in a data mining environment, the data mining environment having a data mining tool and a data mining model, in which the data mining tool scores scoring input data sets using the data mining model to produce scoring output data and store the scoring output data in records in model scoring results tables. Exemplary embodiments include registering the model scoring results tables in a model scoring results control table, in which the registering includes model scoring results table metadata, selecting from among the model scoring results tables a selected model scoring results table, in which the selecting is carried out in dependence upon metadata from the model scoring results control table, reading a scoring output data record from the selected registered model scoring results table, and storing the scoring output data record in a managed representation table.

Abstract: Managing a data mining environment, the data mining environment having a data mining tool and a data mining model. Embodiments include registering in a data set control table registered data sets, the registered data sets including the model training input data sets, model training results data sets, the scoring input data sets, and the scoring output data sets, registering the data mining model in a mining model control table, the mining model control table being related to the data set control table through a mining model control table foreign key, and registering the scoring output data sets in a scoring control table, the scoring control table being related to the data set control table through a scoring control table data set foreign key, the scoring control table being related to the mining model control table through a scoring control table mining model foreign key.

Abstract: Exemplary embodiments typically include methods of deploying a predefined data warehouse process model from a development system having a development environment to a customer system having a customer environment, the customer environment being different from the development environment. Embodiments typically include exporting metadata from the predefined warehouse process model to an interchange metadata file, in which the metadata comprises data elements describing a development environment, in which the metadata comprises at least some data elements having values that are site dependent, and copying, from the interchange metadata file to an interchange resource file, site dependent data elements. Embodiments typically include identifying site dependent data values of the customer system, converting, in the interchange metadata file, the site dependent data element values to the site dependent data values of the customer system, and importing the interchange metadata file into the customer system.