Generating data visualizations according to an object model of selected data sources

Patent metadata

Field	Value
Publication number	US-11966568-B2
Application number	US-201816236611-A
Country	US
Kind code	B2
Filing date	Dec 30, 2018
Priority date	Oct 22, 2018
Publication date	Apr 23, 2024
Grant date	Apr 23, 2024

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.

First claim

What is claimed is:

1. A method of generating data visualizations, comprising:
at a computer having a display, one or more processors, and memory storing one or more programs configured for execution by the one or more processors:
receiving a visual specification, which specifies a data source, a plurality of visual variables, and a plurality of data fields from the data source, wherein each of the visual variables is associated with a respective one or more of the data fields and each of the data fields is identified as either a dimension data field or a measure data field;
identifying an object model of the data source, each object in the object model having a respective primary key;
from the object model, identifying a minimal subtree that includes all of the dimension data fields;
constructing a query from the minimal subtree that accesses the dimension data fields, the minimal subtree including a root node and all other objects in the minimal subtree are reachable from the root node by a sequence of relationships between primary keys and foreign keys of objects in the object model;
executing the query against the data source to retrieve a set of tuples, each tuple in the set of tuples comprising a unique ordered combination of data values for the dimension data fields and forming a distinct data row in a data table for generating a data visualization;
for each measure data field, extending the set of tuples by inserting an additional column in the data table whose values are aggregated data values corresponding to the respective measure data field; and
building and displaying the data visualization according to the data fields in the extended set of tuples and according to the visual variables to which each of the data fields is associated.

2. The method of claim 1 , wherein the visual specification further includes one or more additional visual variables that are not associated with any data fields from the data source.

3. The method of claim 1 , wherein the aggregated data values corresponding to each measure data field are aggregated according to the dimension data fields.

4. The method of claim 1 , further comprising displaying the data visualization in a graphical user interface for the computer.

5. The method of claim 4 , wherein displaying the data visualization comprises generating a plurality of visual marks, each of the visual marks corresponding to a respective extended tuple.

6. The method of claim 4 , wherein the graphical user interface includes a data visualization region, the method further comprising displaying the data visualization in the data visualization region.

7. The method of claim 1 , wherein each of the visual variables is selected from the group consisting of: rows attribute, columns attribute, filter attribute, color encoding, size encoding, shape encoding, and label encoding.

8. The method of claim 1 , wherein the aggregated data values are computed using an aggregate function selected from the group consisting of: SUM, COUNT, COUNTD, MIN, MAX, AVG, MEDIAN, ATTR, PERCENTILE, STDEV, STDEVP, VAR, and VARP.

9. The method of claim 1 , wherein the plurality of data fields are from a plurality of distinct tables in the data source.

10. The method of claim 1 , wherein the object model of the data source has a plurality of objects, and the plurality of data fields belong to two or more distinct objects of the plurality of objects.

11. The method of claim 1 , wherein the visual specification specifies a plurality of data sources, the visual specification specifies one or more data fields from each of the plurality of data sources, and the object model is an object model for the plurality of data sources.

12. A computer system for generating data visualizations, comprising:
a display;
one or more processors; and
memory;
wherein the memory stores one or more programs configured for execution by the one or more processors, and the one or more programs comprising instructions for:
receiving a visual specification, which specifies a data source, a plurality of visual variables, and a plurality of data fields from the data source, wherein each of the visual variables is associated with a respective one or more of the data fields and each of the data fields is identified as either a dimension data field or a measure data field;
identifying an object model of the data source, each object in the object model having a respective primary key;
from the object model, identifying a minimal subtree that includes all of the dimension data fields;
constructing a query from the minimal subtree that accesses the dimension data fields, the minimal subtree including a root node and all other objects in the minimal subtree are reachable from the root node by a sequence of relationships between primary keys and foreign keys of objects in the object model;
executing the query against the data source to retrieve a set of tuples, each tuple in the set of tuples comprising a unique ordered combination of data values for the dimension data fields and forming a distinct data row in a data table for generating a data visualization;
for each measure data field, extending the set of tuples by inserting an additional column in the data table whose values are aggregated data values corresponding to the respective measure data field; and
building and displaying the data visualization according to the data fields in the extended set of tuples and according to the visual variables to which each of the data fields is associated.

13. The computer system of claim 12 , wherein the visual specification further includes one or more additional visual variables that are not associated with any data fields from the data source.

14. The computer system of claim 12 , wherein the aggregated data values corresponding to each measure data field are aggregated according to the dimension data fields.

15. The computer system of claim 12 , wherein the one or more programs further comprise instructions for:
generating a plurality of visual marks, each of the visual marks corresponding to a respective extended tuple; and
displaying the data visualization in a graphical user interface for the computer system.

16. The computer system of claim 12 , wherein each of the visual variables is selected from the group consisting of: rows attribute, columns attribute, filter attribute, color encoding, size encoding, shape encoding, and label encoding.

17. The computer system of claim 12 , wherein the plurality of data fields are from a plurality of distinct tables in the data source.

18. The computer system of claim 12 , wherein the object model of the data source has a plurality of objects, and the plurality of data fields belong to two or more distinct objects of the plurality of objects.

19. The computer system of claim 12 , wherein the visual specification specifies a plurality of data sources, the visual specification specifies one or more data fields from each of the plurality of data sources, and the object model is an object model for the plurality of data sources.

20. A non-transitory computer-readable storage medium storing one or more programs configured for execution by a computer system having a display, one or more processors, and memory, the one or more programs comprising instructions for:
receiving a visual specification, which specifies a data source, a plurality of visual variables, and a plurality of data fields from the data source, wherein each of the visual variables is associated with a respective one or more of the

Assignees

• Tableau Software Inc

Inventors

• Talbot Justin
• Hau Roger
• Cory daniel
• Oh Jiyoung
• Roberts Teresa

Classifications

• G06T11/26

  Drawing of charts or graphs · CPC title

• G06F16/26 Primary

  Visual data mining; Browsing structured data · CPC title

• G06F3/04842 Primary

  Selection of displayed objects or displayed text elements (G06F3/0482 takes precedence) · CPC title

• G06F3/04845

  for image manipulation, e.g. dragging, rotation, expansion or change of colour · CPC title

• G06F3/0486

  Drag-and-drop · CPC title