Abstract: Text including at least a first term can be presented on a display. An enterprise glossary can be queried to identify at least a first curation parameter assigned to the first term. A first score can be determined for the first term based, at least in part, on the first curation parameter assigned to the first term. The first score can be assigned to a first data value. The first data value can be presented on the display.

Abstract: Text including at least a first term can be presented on a display. A first score can be determined for the first term. The first score can be based, at least in part, on a lifecycle of the first term. The first score can be assigned to a first data value. The first data value can be presented on the display.

Abstract: Text including at least a first term can be presented on a display. An enterprise glossary can be queried to identify at least a first curation parameter assigned to the first term. A first score can be determined for the first term based, at least in part, on the first curation parameter assigned to the first term. The first score can be assigned to a first data value. The first data value can be presented on the display.

Abstract: Text including at least a first term can be presented on a display. A first score can be determined for the first term. The first score can be based, at least in part, on a lifecycle of the first term. The first score can be assigned to a first data value. The first data value can be presented on the display.

Abstract: Text including at least a first term can be presented on a display. A first score can be determined for the first term. The first score can be based, at least in part, on a lifecycle of the first term. The first score can be assigned to a first data value. The first data value can be presented on the display.

Abstract: Text including at least a first term can be presented on a display. An enterprise glossary is queried to identify other terms that match the first term. Data assets to which each of the other terms are linked and which include data values for the other terms can be identified. A first score indicating a level of relevance of the respective data asset to an enterprise is assigned to each of the data assets. A frequency distribution of the data values in the data assets is determined. Based at least on the first scores indicating the level of relevance of the respective data assets to the enterprise and the frequency distribution of the data values in the data assets, second scores are assigned to each of the data values. A plurality the data values which are assigned highest of the second scores are presented on the display.

Abstract: Optimizing operational costs in a computing environment includes identifying high-cost jobs that are executed to generate one or more reports in the computing environment, identifying one or more reports the generation of which is dependent on the execution of the high-cost jobs, and culling at least a first job from among the high-cost jobs, in response to determining that a benefit achieved from the reports that depend on the first job does not justify costs associated with generating the reports.

Abstract: Optimizing operational costs in a computing environment includes identifying high-cost jobs that are executed to generate one or more reports in the computing environment, identifying one or more reports the generation of which is dependent on the execution of the high-cost jobs, and culling at least a first job from among the high-cost jobs, in response to determining that a benefit achieved from the reports that depend on the first job does not justify costs associated with generating the reports.

Abstract: Text including at least a first term can be presented on a display. A first score can be determined for the first term. The first score can be based, at least in part, on a lifecycle of the first term. The first score can be assigned to a first data value. The first data value can be presented on the display.

Abstract: Text including at least a first term can be presented on a display. An enterprise glossary is queried to identify other terms that match the first term. Data assets to which each of the other terms are linked and which include data values for the other terms can be identified. A first score indicating a level of relevance of the respective data asset to an enterprise is assigned to each of the data assets. A frequency distribution of the data values in the data assets is determined. Based at least on the first scores indicating the level of relevance of the respective data assets to the enterprise and the frequency distribution of the data values in the data assets, second scores are assigned to each of the data values. A plurality the data values which are assigned highest of the second scores are presented on the display.

Abstract: Optimizing operational costs in a computing environment includes identifying high-cost jobs that are executed to generate one or more reports in the computing environment, identifying one or more reports the generation of which is dependent on the execution of the high-cost jobs, and culling at least a first job from among the high-cost jobs, in response to determining that a benefit achieved from the reports that depend on the first job does not justify costs associated with generating the reports.

Abstract: Optimizing operational costs in a computing environment includes identifying high-cost jobs that are executed to generate one or more reports in the computing environment, identifying one or more reports the generation of which is dependent on the execution of the high-cost jobs, and culling at least a first job from among the high-cost jobs, in response to determining that a benefit achieved from the reports that depend on the first job does not justify costs associated with generating the reports.

Abstract: Optimizing operational costs in a computing environment includes identifying high-cost jobs that are executed to generate one or more reports in the computing environment, identifying one or more reports the generation of which is dependent on the execution of the high-cost jobs, and culling at least a first job from among the high-cost jobs, in response to determining that a benefit achieved from the reports that depend on the first job does not justify costs associated with generating the reports.

Abstract: Optimizing operational costs in a computing environment includes identifying high-cost jobs that are executed to generate one or more reports in the computing environment, identifying one or more reports the generation of which is dependent on the execution of the high-cost jobs, and culling at least a first job from among the high-cost jobs, in response to determining that a benefit achieved from the reports that depend on the first job does not justify costs associated with generating the reports.

Abstract: Text including at least a first term can be presented on a display. An enterprise glossary is queried to identify other terms that match the first term. Data assets to which each of the other terms are linked and which include data values for the other terms can be identified. A first score indicating a level of relevance of the respective data asset to an enterprise is assigned to each of the data assets. A frequency distribution of the data values in the data assets is determined. Based at least on the first scores indicating the level of relevance of the respective data assets to the enterprise and the frequency distribution of the data values in the data assets, second scores are assigned to each of the data values. A plurality the data values which are assigned highest of the second scores are presented on the display.

Abstract: Text including at least a first term can be presented on a display. An enterprise glossary is queried to identify other terms that match the first term. Data assets to which each of the other terms are linked and which include data values for the other terms can be identified. A first score indicating a level of relevance of the respective data asset to an enterprise is assigned to each of the data assets. A frequency distribution of the data values in the data assets is determined. Based at least on the first scores indicating the level of relevance of the respective data assets to the enterprise and the frequency distribution of the data values in the data assets, second scores are assigned to each of the data values. A plurality the data values which are assigned highest of the second scores are presented on the display.

Abstract: A computer implemented system for automatically determining a reliability score of a data report. The system includes a data structure indicative of data lineage that includes data assets flowing into a data report. The system further includes a processor configured to calculate trust scores for data assets based on characteristics of the data assets as well as a data report trust density score indicative of the reliability score of the report based on the calculated trust scores. The system further includes an output device configured to output the calculated data report trust density score.

Abstract: Optimizing operational costs in a computing environment includes identifying high-cost jobs that are executed to generate one or more reports in the computing environment, identifying one or more reports the generation of which is dependent on the execution of the high-cost jobs, and culling at least a first job from among the high-cost jobs, in response to determining that a benefit achieved from the reports that depend on the first job does not justify costs associated with generating the reports.

Abstract: A computer implemented system for automatically determining a reliability score of a data report. The system includes a data structure indicative of data lineage that includes data assets flowing into a data report. The system further includes a processor configured to calculate trust scores for data assets based on characteristics of the data assets as well as a data report trust density score indicative of the reliability score of the report based on the calculated trust scores. The system further includes an output device configured to output the calculated data report trust density score.

Abstract: Presenting data lineage information by assigning a score to a data asset along a path between a data source and a data destination, where a predefined scoring function is applied to a characteristic of the data asset, and presenting via a computer-controlled output medium a description of the data source, the data destination, and the path between the data source and the data destination, where the description includes the data asset if the score meets predefined inclusion criteria.