Abstract: Aspects extend to methods, systems, and computer program products for ranking contextual metadata to generate relevant data insights. Aspects of the invention can be used to enhance data analytics by automatically deriving relevance signals used to generate insights closely related to the context in which a user is exploring or analyzing data. User experiences can include embedded data visualizations, search engines, and natural language querying systems to help users understand their data more effectively. By utilizing metrics on the relevance information, insights related and/or relevant to the context in which the user is analyzing data can be created. Thus, relevance information can define a scope for a variety of automatically generated insights of data. Insight generation can be based on computed relevance signals that target areas interesting to users.

Abstract: Aspects extend to methods, systems, and computer program products for ranking contextual metadata to generate relevant data insights. Aspects of the invention can be used to enhance data analytics by automatically deriving relevance signals used to generate insights closely related to the context in which a user is exploring or analyzing data. User experiences can include embedded data visualizations, search engines, and natural language querying systems to help users understand their data more effectively. By utilizing metrics on the relevance information, insights related and/or relevant to the context in which the user is analyzing data can be created. Thus, relevance information can define a scope for a variety of automatically generated insights of data. Insight generation can be based on computed relevance signals that target areas interesting to users.

Abstract: Aspects extend to methods, systems, and computer program products for ranking contextual metadata to generate relevant data insights. Aspects of the invention can be used to enhance data analytics by automatically deriving relevance signals used to generate insights closely related to the context in which a user is exploring or analyzing data. User experiences can include embedded data visualizations, search engines, and natural language querying systems to help users understand their data more effectively. By utilizing metrics on the relevance information, insights related and/or relevant to the context in which the user is analyzing data can be created. Thus, relevance information can define a scope for a variety of automatically generated insights of data. Insight generation can be based on computed relevance signals that target areas interesting to users.

Abstract: Analyzing data. A method includes obtaining a set of a plurality of data entities and relationships. The method further includes subdividing the set of a plurality of data entities and relationships into a plurality of composite collections of data entities and relationships. Each composite collection within the plurality of composite collections disambiguates the composite collection, within a relationship scope, from ambiguities in the set of a plurality of data entities and relationships. The method further includes providing one or more of the plurality of composite collections of data entities and relationships to a data mining engine. Each composite collection of data entities and relationships is provided as a separate unit to the data mining engine.

Abstract: Aspects extend to methods, systems, and computer program products for ranking contextual metadata to generate relevant data insights. Aspects of the invention can be used to enhance data analytics by automatically deriving relevance signals used to generate insights closely related to the context in which a user is exploring or analyzing data. User experiences can include embedded data visualizations, search engines, and natural language querying systems to help users understand their data more effectively. By utilizing metrics on the relevance information, insights related and/or relevant to the context in which the user is analyzing data can be created. Thus, relevance information can define a scope for a variety of automatically generated insights of data. Insight generation can be based on computed relevance signals that target areas interesting to users.

Abstract: Analyzing data. A method includes obtaining a set of a plurality of data entities and relationships. The method further includes subdividing the set of a plurality of data entities and relationships into a plurality of composite collections of data entities and relationships. Each composite collection within the plurality of composite collections disambiguates the composite collection, within a relationship scope, from ambiguities in the set of a plurality of data entities and relationships. The method further includes providing one or more of the plurality of composite collections of data entities and relationships to a data mining engine. Each composite collection of data entities and relationships is provided as a separate unit to the data mining engine.

Abstract: Described are methods and apparatus that allow viewers to access timely data showing what other viewers are watching at (or near) a given moment. Thus, for example, a viewer could tune in, find out which ten programs currently being broadcast are most popular, and then select from among these programs. In one embodiment, the data is displayed with links to those popular programs so viewers can easily tune to listed programs. In another embodiment, the viewer can identify a group of friends and find out what those friends are watching. The viewer could then tune into one of the programs his or her friends are watching, and so be prepared to discuss that program later.