Abstract: Data classification includes tracking classification of columns of data into data classes of a collection of classes available for classifying the columns, obtaining a target column of data, of a target dataset, to be classified into a data class of the collection of candidate classes, and classifying the target column of data into a data class of the collection of classes based on historical data classification characteristics provided by the tracking. The classifying includes selecting a group of candidate data classes of the collection of classes to compare to value(s) of the target column, the selecting excludes at least some candidate data classes of the collection from comparison to the value(s), and establishing a priority between the candidate data classes of the group of candidate classes in comparing the value(s) of the target column of data to the selected group of candidate classes.

Abstract: A method provides for classifying data fields of a dataset. A classifier configured for determining confidence values for a plurality of data classes for the data fields may be applied. Using the confidence values, data class candidates may be identified. Data fields may be determined for which a plurality of data class candidates is identifiable. Using previous user-selected data class assignments, a probability may be determined for the data class candidates that the respective data class candidate is a data class to which the respective data field is to be assigned. The data fields may be classified using the probabilities to select for the data fields a data class from the data class candidates. The dataset may be provided with metadata identifying for the data fields the data classes to which the respective data fields are assigned.

Abstract: A computer system, computer program product, and a computer-implemented method for supplementing a data governance framework with one or more new data governance technical rules is disclosed. The method comprises providing a plurality of expressions and a first mapping. The expressions assign natural language patterns to technical language patterns. The first mapping maps first terms to data sources. A rule generator receives a new natural language (NL) rule comprising one or more natural-language patterns and one or more first terms. The rule generator resolves the new NL rule into one or more new technical rules interpretable by a respective rule engine and stores the one or more technical rules in a rule repository.

Abstract: The invention relates to computer-implemented method for supplementing a data governance framework with one or more new data governance technical rules. The method comprises providing a plurality of expressions and a first mapping. The expressions assign natural language patterns to technical language patterns. The first mapping maps first terms to data sources. A rule generator receives a new natural language (NL) rule comprising one or more natural-language patterns and one or more first terms. The rule generator resolves the new NL rule into one or more new technical rules interpretable by a respective rule engine and stores the one or more technical rules in a rule repository.

Abstract: The present disclosure relates to a method for creating run-time executables for data analysis functions. The method comprises in response to receiving a data analysis request from a user, selecting from a repository a repository of data analysis functions a set of data analysis functions for execution in a hosting environment or on premises of the user. Usage conditions of the set of data analysis functions by the user may be determined. An additional code for applying the determined usage conditions may be created. The selected data analysis functions and the additional code may be compiled, resulting in an executable code. The executable code may be certified. The certified executable code may be deployed or provided for download to a run-time environment for certified executable codes.

Abstract: The present disclosure relates to a method for creating run-time executables for data analysis functions. The method comprises in response to receiving a data analysis request from a user, selecting from a repository a repository of data analysis functions a set of data analysis functions for execution in a hosting environment or on premises of the user. Usage conditions of the set of data analysis functions by the user may be determined. An additional code for applying the determined usage conditions may be created. The selected data analysis functions and the additional code may be compiled, resulting in an executable code. The executable code may be certified. The certified executable code may be deployed or provided for download to a run-time environment for certified executable codes.

Abstract: The invention relates to computer-implemented method for supplementing a data governance framework with one or more new data governance technical rules. The method comprises providing a plurality of expressions and a first mapping. The expressions assign natural language patterns to technical language patterns. The first mapping maps first terms to data sources. A rule generator receives a new natural language (NL) rule comprising one or more natural-language patterns and one or more first terms. The rule generator resolves the new NL rule into one or more new technical rules interpretable by a respective rule engine and stores the one or more technical rules in a rule repository.

Abstract: The invention relates to computer-implemented method for supplementing a data governance framework with one or more new data governance technical rules. The method comprises providing a plurality of expressions and a first mapping. The expressions assign natural language patterns to technical language patterns. The first mapping maps first terms to data sources. A rule generator receives a new natural language (NL) rule comprising one or more natural-language patterns and one or more first terms. The rule generator resolves the new NL rule into one or more new technical rules interpretable by a respective rule engine and stores the one or more technical rules in a rule repository.

Abstract: The invention relates to computer-implemented method for supplementing a data governance framework with one or more new data governance technical rules. The method comprises providing a plurality of expressions and a first mapping. The expressions assign natural language patterns to technical language patterns. The first mapping maps first terms to data sources. A rule generator receives a new natural language (NL) rule comprising one or more natural-language patterns and one or more first terms. The rule generator resolves the new NL rule into one or more new technical rules interpretable by a respective rule engine and stores the one or more technical rules in a rule repository.