Abstract: A method, system and computer program product for generating instances of dashboards, each dashboard instance including a set of visualizations of analytical data, relating to a collection of data. User interaction data representative of a user's actions undertaken during data exploration of the collection of data is obtained. A set of potential visualizations of analytical data relating to the collection of data is defined based on the user interaction data. At least one dashboard instance relating to the collection of data is defined based on the user interaction data and the set of potential visualizations.

Abstract: A method, system and computer program product for generating instances of dashboards, each dashboard instance including a set of visualizations of analytical data, relating to a collection of data. User interaction data representative of a user's actions undertaken during data exploration of the collection of data is obtained. A set of potential visualizations of analytical data relating to the collection of data is defined based on the user interaction data. At least one dashboard instance relating to the collection of data is defined based on the user interaction data and the set of potential visualizations.

Abstract: A method for assessing a quality of a plurality of changes to a plurality of source code is provided. The method may include receiving the plurality of source code for a software product, whereby the received plurality of source code includes the plurality of changes. The method may also include identifying at least one property associated with each of the plurality of changes within the received plurality of source code. The method may further include determining a confidence level for each of the plurality of changes based on the at least one identified property associated with each of the plurality of changes and a plurality of historical software build data. The method may also include assigning each of the plurality of changes to a build group based on the determined confidence level. The method may further include executing the build group in a software build.

Abstract: A method, system and computer program product for generating instances of dashboards, each dashboard instance including a set of visualizations of analytical data, relating to a collection of data. User interaction data representative of a user's actions undertaken during data exploration of the collection of data is obtained. A set of potential visualizations of analytical data relating to the collection of data is defined based on the user interaction data. At least one dashboard instance relating to the collection of data is defined based on the user interaction data and the set of potential visualizations.

Abstract: A method, system and computer program product for generating instances of dashboards, each dashboard instance including a set of visualizations of analytical data, relating to a collection of data. User interaction data representative of a user's actions undertaken during data exploration of the collection of data is obtained. A set of potential visualizations of analytical data relating to the collection of data is defined based on the user interaction data. At least one dashboard instance relating to the collection of data is defined based on the user interaction data and the set of potential visualizations.

Abstract: A method for assessing a quality of a plurality of changes to a plurality of source code is provided. The method may include receiving the plurality of source code for a software product, whereby the received plurality of source code includes the plurality of changes. The method may also include identifying at least one property associated with each of the plurality of changes within the received plurality of source code. The method may further include determining a confidence level for each of the plurality of changes based on the at least one identified property associated with each of the plurality of changes and a plurality of historical software build data. The method may also include assigning each of the plurality of changes to a build group based on the determined confidence level. The method may further include executing the build group in a software build.

Abstract: A computer executable chart visualization may be generated from a static image of the chart visualization. The static image, a set of pre-defined chart elements, and a portion of the static image that corresponds to a pre-defined chart element may each be identified. A mapping between the portion of the static image and the pre-defined chart elements may be determined, and a visual or logical property of each portion of the static image may be determined. A declarative description of the chart visualization may be generated by setting the visual properties for each of the respective pre-defined chart elements.

Abstract: A declarative specification for visualization may be improved. The declarative specification for the visualization may be identified and checked for appropriateness. This appropriateness check can be done by ensuring that the declarative specification meets a number of rules. The rules may be predefined and include rules that define best practices for visualizations. If a portion of the declarative specification violates one of the rules, it can be highlighted. In this way, the user can see how the declarative specification can be improved for visualization.

Abstract: A computer executable chart visualization may be generated from a static image of the chart visualization. The static image, a set of pre-defined chart elements, and a portion of the static image that corresponds to a pre-defined chart element may each be identified. A mapping between the portion of the static image and the pre-defined chart elements may be determined, and a visual or logical property of each portion of the static image may be determined. A declarative description of the chart visualization may be generated by setting the visual properties for each of the respective pre-defined chart elements.

Abstract: A declarative specification for visualization may be improved. The declarative specification for the visualization may be identified and checked for appropriateness. This appropriateness check can be done by ensuring that the declarative specification meets a number of rules. The rules may be predefined and include rules that define best practices for visualizations. If a portion of the declarative specification violates one of the rules, it can be highlighted. In this way, the user can see how the declarative specification can be improved for visualization.