Abstract: A method displays a first data visualization according to user association of data fields with displayed data visualization properties. The data visualization includes visual data marks corresponding to data values for data fields in a dataset. A user selects a subset of the visual data marks. A popup summary is displayed that includes data value distributions for several data fields from the dataset. In the popup summary, a second user input is detected corresponding to a first data field whose data value distribution is displayed in the popup summary. The second user input associates the first data field with a first visualization property of the displayed data visualization properties. In response, a second data visualization is displayed according to association of data fields, including the first data field, with displayed data visualization properties.

Abstract: A method displays a graphical user interface for a data visualization application. The user interface includes a schema information region that includes fields from a database. A user specifies a first aggregation using the interface. The first aggregation groups by a first set of fields and specifies an aggregated output field. The user also specifies a second aggregation. The second aggregation references the first aggregation and groups by a second set of fields. The set may include the aggregated output field. The second set is different from the first set. The method builds a visual specification based on the first and second aggregations. The method may retrieve tuples of data from the database using database queries generated from the visual specification, where each tuple includes data calculated based on the second aggregation. The method may display a data visualization, including the data calculated based on the second aggregation.

Abstract: A database engine receives a query batch of database queries from a client. The database engine identifies one or more object model queries from the query batch. Each object model query includes an outer-most outer-join that joins a respective dimension subquery and respective aggregated measure subqueries. The database engine forms a plurality of candidate subqueries by peeling off the respective outer-most outer-join for each of the object model queries. The database engine then fuses at least some of the plurality of candidate subqueries to form a set of optimized subqueries. The set of optimized subqueries has fewer subqueries than the plurality of candidate queries. The database engine also forms an optimized execution plan based on the set of one or more optimized subqueries. The database engine subsequently obtains a result set from the database based on the optimized execution plan, and returns the result set to the client.

Abstract: A method displays a chart that includes visual marks representing a data set, displayed according to contents of displayed shelf regions, which determine characteristics of the chart. The method detects selection of a plurality of visual marks, and visually emphasizes the selected plurality of visual marks. The method also detects a first input on the selected marks, and displays a moveable icon corresponding to the selected visual marks while maintaining display of the visual marks. The method detects a second input on the moveable icon, and moves the moveable icon over a first shelf region. Upon ceasing to detect the input, the method updates the content of the first shelf region based on the selected visual marks, and updates the chart in accordance with updated content of the first shelf region, including applying the characteristic of the first shelf to the selected visual marks distinct from the unselected visual marks.

Abstract: A computing device displays a data visualization interface and receives user selection of a data source. The computing device also receives user input to select a measure data field and a dimension data field. In response to the user input, the computing device: generates a custom calculation that aggregates data for the measure data field, grouped by distinct data values of the dimension data field; and stores the custom calculation as a new selectable data field, associated with a data object corresponding to the dimension data field. The computing device also receives user selection of the new selectable data field and placement of the new selectable data field onto a first shelf in a shelf region. The first shelf defines a first data visualization characteristic determined according to data values of the custom calculation. The computing device generates and displays a data visualization based on the first data visualization characteristic.

Abstract: A method displays a first data visualization according to user placement of data fields in shelves of a user interface. Each shelf specifies a property of the data visualization and the data visualization includes visual data marks corresponding to data values for data fields in a dataset. A user selects a subset of the visual data marks. A popup summary is displayed that includes data value distributions for several data fields. In the popup summary, a second user input is detected corresponding to a first data field whose data value distribution is displayed in the popup summary. In response, the method displays a moveable icon corresponding to the first data field. The method detects a third user input to place the interactive moveable icon in a shelf in the user interface. In response, a second data visualization is displayed according to placement of data fields, including the first data field.

Abstract: A computer receives a visual specification, which specifies a data source, visual variables, and data fields from the data source. Each visual variable is associated with either data fields or filters. The computer obtains a data model encoding the data source as a tree of related logical tables. Each logical table includes logical fields that corresponds to either a data field or a calculation that spans logical tables. The computer constructs a query corresponding to the visual specification. The query references two logical tables connected via multiple linking fields. To generate the query, the computer generates a first left-outer join of the two tables, forms a hidden join key expression using a coalesce, according to the data model, and generates another left-outer join using the hidden join key expression. The computer executes the query and displays a data visualization according to the results of the query.

Abstract: A user selects a data source, and a computer displays a data visualization in a data visualization user interface according to the data source. The data visualization includes visual data marks representing data from the data source. The user selects a subset of the visual data marks. In response, the computer displays a view data window having a summary of the selected data marks. The computer obtains a data model encoding the data source as a tree of logical tables. The computer identifies aggregate measures corresponding to the selected data marks, where each aggregate measure is aggregated from logical tables of the data model. The computer displays each aggregate measure in the view data window. The computer also displays, in the view data window, one or more level of detail calculations referenced in the selected subset of visual data marks.

Abstract: A user selects a data source, and a computer displays a data visualization in a data visualization user interface according to the data source. The data visualization includes visual data marks representing data from the data source. The user selects a subset of the visual data marks. In response, the computer displaying a view data window having a summary of the selected data marks. The computer obtains a data model encoding the data source as a tree of logical tables, each including one or more logical fields. Each logical field corresponds to either a data field or a calculation that spans one or more logical tables. Each edge of the tree connects two logical tables that are related. The computer identifies aggregate measures corresponding to the selected data marks, and displays each aggregate measure in the view data window.

Abstract: A method displays a chart that includes visual marks representing a data set, displayed according to contents of displayed shelf regions, which determine characteristics of the chart. The method detects selection of a plurality of visual marks, and visually emphasizes the selected plurality of visual marks. The method also detects a first input on the selected marks, and displays a moveable icon corresponding to the selected visual marks while maintaining display of the visual marks. The method detects a second input on the moveable icon, and moves the moveable icon over a first shelf region. Upon ceasing to detect the input, the method updates the content of the first shelf region based on the selected visual marks, and updates the chart in accordance with updated content of the first shelf region, including applying the characteristic of the first shelf to the selected visual marks distinct from the unselected visual marks.

Abstract: A user selects a data source, and a computer displays a data visualization in a data visualization user interface according to the data source. The data visualization includes visual data marks representing data from the data source. The user selects a subset of the visual data marks. In response, the computer displaying a view data window having a summary of the selected data marks. The computer obtains a data model encoding the data source as a tree of logical tables, each including one or more logical fields. Each logical field corresponds to either a data field or a calculation that spans one or more logical tables. Each edge of the tree connects two logical tables that are related. The computer identifies aggregate measures corresponding to the selected data marks, and displays each aggregate measure in the view data window.

Abstract: An exemplary method receives user actions to (i) associate a first field with a first shelf and (ii) associate second and third fields with a second shelf. The second field is positioned at an outer-most position on the second shelf and the third field is positioned at an inner-most position on the second shelf. The method receives an additional user action to specify a nested sort according to data for the first and third fields. The method generates and displays a data visualization in accordance with the received actions, including: (i) partitioning retrieved data into groups of tuples, each tuple including data for the fields, and each group of tuples corresponding to a distinct value of the second field, (ii) forming panes, each pane corresponding to a respective group of tuples, and (iii) within each pane, displaying data marks, each data mark corresponding to a respective tuple.

Abstract: A method displays a chart that includes visual marks representing a data set, displayed according to contents of displayed shelf regions, which determine characteristics of the chart. The method detects selection of a plurality of visual marks, and visually emphasizes the selected plurality of visual marks. The method also detects a first input on one of the selected marks, and displays a moveable icon corresponding to the selected visual marks while maintaining display of the visual marks. The method detects a second input on the moveable icon, and moves the moveable icon over a first shelf region. Upon ceasing to detect the input, the method updates the content of the first shelf region based on the selected visual marks, and updates the chart in accordance with updated content of the first shelf region.

Abstract: A method displays a chart including visual marks representing a dataset. The chart is displayed according to contents of multiple shelf regions. The shelf regions determine characteristics of the chart. The method generates a visual analytic object by applying an analytic operation to the set of data represented by the visual marks, and displays the visual analytic object superimposed over the chart. The method detects user input to select the displayed visual analytic object and place an icon representing the visual analytic object onto a first shelf region. In response, the method updates the content of the first shelf region to associate it with the analytic operation corresponding to the visual analytic object and updates the chart according to the updated content of the first shelf region. This includes updating the chart based on values of the dataset represented by the visual marks relative to the analytic operation.

Abstract: A computer receives a visual specification, which specifies a data source, visual variables, and data fields from the data source. Each visual variable is associated with either data fields (e.g., dimension and/or measures) or filters. The computer obtains a data model encoding the data source as a tree of related logical tables. Each logical table includes logical fields, each of which corresponds to either a data field or a calculation that spans logical tables. The computer generates a dimension subquery for the dimensions and the filters. The computer also generates, for each measure, an aggregated measure subquery grouped by the dimensions. The computer forms a final query by joining the dimension subquery to each of the aggregated measure subqueries. The computer subsequently executes the final query and displays a data visualization according to the results of the final query.

Abstract: An exemplary method receives user actions to (i) associate a first field with a first shelf and (ii) associate second and third fields with a second shelf. The second field is positioned at an outer-most position on the second shelf and the third field is positioned at an inner-most position on the second shelf. The method receives an additional user action to specify a nested sort according to data for the first and third fields. The method generates and displays a data visualization in accordance with the received actions, including: (i) partitioning retrieved data into groups of tuples, each tuple including data for the fields, and each group of tuples corresponds to a distinct value of the second field, (ii) forming panes, each pane corresponding to a respective group of tuples, and (iii) within each pane, displaying data marks, each data mark corresponding to a respective tuple.

Abstract: An electronic device displays a chart, which includes visual marks that represent calculated values derived from a set of data, and panes formed by intersection of rows and columns. A current focus is on a first visual mark at a first position. The device concurrently displays a chart-calculations-options area, which includes display options for the type of calculation and the type of data partitioning. Visual marks in a first set of visual marks are visually distinguished from other visual marks. The first set of visual marks includes the first visual mark, and corresponds to a first selected option for the type of calculation and a first selected option for the type of data partitioning. The device detects an input that selects a second option for the type of data partitioning. In response, the device visually distinguishes visual marks in a second set of visual marks in accordance with the selection.

Abstract: A method generates a graphical representation of a data source using a graphical user interface. The user interface includes a schema information region and a data visualization region. The schema information region includes field names associated with data fields. The data visualization region includes shelf regions that determine characteristics of a visual graphic. Each shelf region is configured to receive user placement of field names. The user selects field names and places each field name in a respective shelf region. The user edits a first shelf region, creating a first calculated element in the first shelf region. The first calculated element does not match any of the field names in the schema information region. The method generates a visual graphic based on the content of the shelf regions, including the user-selected field names and the first calculated element, and displays the visual graphic in the data visualization region.

Abstract: The method receives a visual specification, which specifies a data source, visual variables, and data fields from the data source. Each visual variable is associated with data fields and each data field is a dimension or a measure. The method forms dimension tuples comprising distinct ordered combinations of data values for the dimensions D. For each measure, the method: forms a set S of the dimensions D plus dimensions from a primary key corresponding to the measure; retrieves intermediate tuples containing the fields in S and the measure, without aggregation; and aggregates the intermediate tuples according to the dimensions D. For each dimension tuple, the method forms an extended tuple by appending the aggregated data values corresponding to each measure field. The method then builds and displays a data visualization according to the extended tuples and the visual variables to which the data fields are associated.

Abstract: The method receives a visual specification, which specifies a data source, visual variables, and data fields from the data source. Each visual variable is associated with data fields and each data field is either a dimension or a measure. From an object model of the data source, the method identifies a minimal subtree that includes all of the dimension data fields and constructs a query from the minimal subtree. The method executes the query against the data source to retrieve a set of tuples, each tuple comprising a unique ordered combination of data values for the dimension data fields. For each tuple, the method forms an extended tuple by appending aggregated data values corresponding to each measure data field. The method then builds and displays a data visualization according to the data fields in the extended tuples and according to the visual variables to which the data fields are associated.