Abstract: One aspect relates to generating a unifying virtual schema in a non-relational database. A database is analyzed either in its entirety, or in part by using a sample of the database as a representative portion of the database as a whole. Common attributes within the database may be identified, ranked and displayed to a user through one or more of various visualizations. In other examples, the user may further refine the way the data is displayed and how much is displayed by interacting with a user interface.

Abstract: One aspect relates to generating a unifying virtual schema in a non-relational database. A database is analyzed either in its entirety, or in part by using a sample of the database as a representative portion of the database as a whole. Common attributes within the database may be identified, ranked and displayed to a user through one or more of various visualizations. In other examples, the user may further refine the way the data is displayed and how much is displayed by interacting with a user interface.

Abstract: One aspect relates to generating a unifying virtual schema in a non-relational database. A database is analyzed either in its entirety, or in part by using a sample of the database as a representative portion of the database or database portion as a whole. Common attributes within the database may be identified, ranked and displayed to a user through one or more of various visualizations. In other examples, the user may further refine the way the data is displayed and how much is displayed by interacting with a user interface. Another aspect associates visualizations of common attributes and respective data with executable query language. In one embodiment, selections within the UI generate executable queries for the user.

Abstract: One aspect relates to generating a unifying virtual schema in a non-relational database. A database is analyzed either in its entirety, or in part by using a sample of the database as a representative portion of the database as a whole. Common attributes within the database may be identified, ranked and displayed to a user through one or more of various visualizations. In other examples, the user may further refine the way the data is displayed and how much is displayed by interacting with a user interface.

Abstract: A system and method of dynamic compensation for providing content recommendations. When a content recommendation is received from a first user, a first value of the content may be determined at the time related to receipt of the recommendation. A second value of the content may be determined after a first predetermined time period and a third value may be determined that is based on a difference between the first and second values. The third value may be paid to the first user. The first and second values may be indicative of demand over different time periods. Thus, recommenders may be compensated according to the individual success of the content they recommend, as measured by the increase in valuation of the content from the time of recommendation to a later time when the content reaches a threshold valuation or increases a predetermined amount.