Tableau Software, Inc.

Salesforce, Inc.

Jeffrey Mark Booth, Jr

Thomas Nhan

Justin Talbot

Daniel Cory

David Pace

Christian Gabriel Eubank

Amy Nicole Forstrom

Nicolas Ratigan Borden

Russell Steven Paul-Jones

Bethany Meaghan Lyons

Tyler Martin

Alvin Edward Jou

Marian Simo Boitel

Franz Gustave Amador

Jinbo Feng

A computer system displays a data visualization in a data visualization user interface. In response to detecting a user input that selects a subset of visual data marks from the data visualization, the computer system displays a summary of the selected subset of visual data marks in a summary tab of a view data window. When the computer system determines that the selected subset of visual marks (1) corresponds to a plurality of data fields and (2) references a row-level calculation that uses logical fields from at least two logical tables of a plurality of logical tables of a data model, the computer system (i) generates a representation of the row-level calculation and (ii) displays the representation of the row-level calculation as a first tab in the view data window, distinct from the summary tab.

System and method for visually analyzing row-level calculations for data visualizations across multiple data tables including displaying separate tabs for the row-level calculations and visual data marks summary

A computing device receives user input specifying a first dimension data field and a second dimension data field. The device constructs a dimension subquery according to characteristics of the first dimension data field, the second dimension data field, a first object to which the first dimension data field belongs, and/or a second object to which the second dimension data field belongs, including determining a join type for combining (i) first data rows that include data values of the first dimension data field and (ii) second data rows that include data values of the second dimension data field. The device constructs the dimension subquery according to the determined join type, and executes the dimension subquery to retrieve first tuples. The device constructs measure subqueries and executes the measure subqueries to retrieve second tuples. The device forms extended tuples, and generates and displays the data visualization according to the extended tuples.

Query semantics for multi-fact data model analysis using shared dimensions

A computing device generates and displays a data visualization in a data visualization user interface. The data visualization includes a plurality of visual data marks representing data from a data source. The computing device detects a first user input to select a visual data mark of the plurality of visual data marks. In response to detecting the first user input, the computing device identifies a first aggregated data value, for the visual data mark, corresponding to a first data field in the data source. The computing device retrieves a first disaggregated set of data rows corresponding to the first aggregated data value, from a first table, in the data source, containing the first data field. The computing device displays, in the data visualization user interface, a plurality of data rows from the first disaggregated set of data rows.

Using an object model to view data associated with data marks in a data visualization

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.

Methods and user interfaces for visually analyzing data visualizations with row-level calculations

A computing device receives user selection of a data source. The computing device receives a user input to specify a level of detail (LOD) expression, which includes a first keyword, a SORT keyword, and an analytic expression. In response to the user input, the computing device identifies one or more data fields from the data source. The device translates the LOD expression into one or more executable database queries referencing the identified data fields. The computing device executes the queries to retrieve data from the data source. The computing device generates and displays a data visualization using the retrieved data.

Table calculations for visual analytics using concise level of detail semantics

A computer generates and displays a data visualization in a data visualization user interface according to placement of data fields, from a data source. The data visualization includes visual data marks representing data from the data source. The computer detects a user input to select a visual data mark. In response to detecting the user input, the computer obtains a data model encoding the data source as a tree of logical tables. The computer identifies one or more aggregated data values for the visual data mark, each of the aggregated data values corresponding to a respective data field in the data model. For each of the aggregated data values, the computer retrieves a respective disaggregated set of data rows from a respective logical table containing the respective data field. The computer displays a summary grid, with a respective tab corresponding to each of the retrieved disaggregated sets of data rows.

A method generates a data source. A user selects a first data set from a displayed object model of a database. The object model includes data sets linked visually by many-to-one relationships to form a tree. The user selects a data field in the first data set and specifies a filter condition. The system identifies a second data set in the tree, and joins the first and second data sets. When the second data set is related to the first data set via one or more many-to-one relationships, rows of the second data set are joined to rows of the first data set that satisfy the first filter condition. When the second data does not satisfy the condition, the second data set is joined to rows of the first data set that satisfy the first filter condition, and all rows of the second data set are included in the generation.

One way cascading of attribute filters in hierarchical object models

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.

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Seattle, WA, United States of America

Jeffrey Mark Booth, Jr