摘要:
A method for automatically forming the clearest and most useful visual plot for a given dataset of tuples. A best view type is selected for a view that includes a subsequently added new field. The visual plot is populated with the data in the view and then automatically rendered for the user. A dataset that is retrieved from a storage is analyzed to identify all the data types found in the dataset, and to determine the best view type to assign to the dataset's views. The visual plot is then populated with the data according to this best view type, and is automatically rendered for the user.
摘要:
A method for automatically forming the clearest and most useful visual plot for a given dataset of tuples. A best view type is selected for a view that includes a subsequently added new field. The visual plot is populated with the data in the view and then automatically rendered for the user. A dataset that is retrieved from a storage is analyzed to identify all the data types found in the dataset, and to determine the best view type to assign to the dataset's views. The visual plot is then populated with the data according to this best view type, and is automatically rendered for the user.
摘要:
A method for automatically forming the clearest and most useful visual plot for a given dataset of tuples. A best view type is selected for a view that includes a subsequently added new field. The visual plot is populated with the data in the view and then automatically rendered for the user. A dataset that is retrieved from a storage is analyzed to identify all the data types found in the dataset, and to determine the best view type to assign to the dataset's views. The visual plot is then populated with the data according to this best view type, and is automatically rendered for the user.
摘要:
In response to a user request, a computer generates a graphical user interface on a computer display. A schema information region of the graphical user interface includes multiple operand names, each operand name associated with one or more fields of a multi-dimensional database. A data visualization region of the graphical user interface includes multiple shelves. Upon detecting a user selection of the operand names and a user request to associate each user-selected operand name with a respective shelf in the data visualization region, the computer generates a visual table in the data visualization region in accordance with the associations between the operand names and the corresponding shelves. The visual table includes a plurality of panes, each pane having at least one axis defined based on data for the fields associated with a respective operand name.
摘要:
A method and system for producing graphics. A hierarchical structure of a database is determined. A visual table, comprising a plurality of panes, is constructed by providing a specification that is in a language based on the hierarchical structure of the database. In some cases, this language can include fields that are in the database schema. The database is queried to retrieve a set of tuples in accordance with the specification. A subset of the set of tuples is associated with a pane in the plurality of panes.
摘要:
A method and system for producing graphics. A hierarchical structure of a database is determined. A visual table, comprising a plurality of panes, is constructed by providing a specification that is in a language based on the hierarchical structure of the database. In some cases, this language can include fields that are in the database schema. The database is queried to retrieve a set of tuples in accordance with the specification. A subset of the set of tuples is associated with a pane in the plurality of panes.
摘要:
A method for forming a visual plot using a hierarchical structure of a dataset. The dataset comprises a measure and a dimension. The dimension consists of a plurality of levels. The plurality of levels form a dimension hierarchy. The visual plot is constructed based on a specification. A first level from the plurality of levels is represented by a first component of the visual plot. A second level from the plurality of levels is represented by a second component of the visual plot. The dataset is queried to retrieve data in accordance with the specification. The data includes all or a portion of the dimension and all or a portion of the measure. The visual plot is populated with the retrieved data in accordance with the specification.
摘要:
A method for forming a visual plot using a hierarchical structure of a dataset. The dataset comprises a measure and a dimension. The dimension consists of a plurality of levels. The plurality of levels form a dimension hierarchy. The visual plot is constructed based on a specification. A first level from the plurality of levels is represented by a first component of the visual plot. A second level from the plurality of levels is represented by a second component of the visual plot. The dataset is queried to retrieve data in accordance with the specification. The data includes all or a portion of the dimension and all or a portion of the measure. The visual plot is populated with the retrieved data in accordance with the specification.
摘要:
A method for forming a visual plot using a hierarchical structure of a dataset. The dataset comprises a measure and a dimension. The dimension consists of a plurality of levels. The plurality of levels form a dimension hierarchy. The visual plot is constructed based on a specification. A first level from the plurality of levels is represented by a first component of the visual plot. A second level from the plurality of levels is represented by a second component of the visual plot. The dataset is queried to retrieve data in accordance with the specification. The data includes all or a portion of the dimension and all or a portion of the measure. The visual plot is populated with the retrieved data in accordance with the specification.
摘要:
A method of automatically generating models from a dataset includes multiple steps. First, a description of a view of a dataset is provided. The description includes multiple fields associated with the dataset. Next, a set of properties is determined for each of the multiple fields. Finally, the description is automatically translated into one or more models based on the respective properties of the multiple fields and a set of predefined heuristics.